TU Wien Informatics

20 Years

Allan Hanbury

Univ.Prof. Dr.

Research Focus

Research Areas

  • Information Retrieval, Data Mining, Information Extraction
Allan Hanbury

About

Allan Hanbury is Professor for Data Intelligence, head of the Data Science Research Unit, and Faculty Representative (responsible for financial affairs and internationalisation) at the Faculty of Informatics, TU Wien, Austria. He is also faculty member of the Complexity Science Hub Vienna.

He was scientific coordinator of the EU-funded Khresmoi Project on medical and health information search and analysis, and is co-founder of contextflow, the spin-off company commercialising the radiology image search technology developed in the Khresmoi project. He is coordinator of DoSSIER, a Marie Curie Innovative Training Network, educating 15 doctoral students on domain-specific systems for information extraction and retrieval. He also coordinated the EU-funded VISCERAL project on evaluation of algorithms on big data, and the EU-funded KConnect project on technology for analysing medical text. He is author or co-author of over 180 publications in refereed journals and refereed international conferences. He contributes to research and innovation strategy development in Austria and Europe, and regularly gives talks on topics related to his research.

Roles

  • Faculty Representative
    Financial Affairs and Internationalization
    Office of the Dean, E199-01
  • Head of Research Unit
    Data Science, E194-04
  • Full Professor
    Data Science, E194-04
  • Curriculum Coordinator
    Double-Degree Program INSA Lyon/TU Wien

2023

2022

  • Professional Search in Context / Hanbury, A. (2022, November 2). Professional Search in Context [Presentation]. University of Queensland, Brisbane, Australia. http://hdl.handle.net/20.500.12708/153988
  • Introducing Neural Bag of Whole-Words with ColBERTer: Contextualized Late Interactions using Enhanced Reduction / Hofstätter, S., Khattab, O., Althammer, S., Sertkan, M., & Hanbury, A. (2022). Introducing Neural Bag of Whole-Words with ColBERTer: Contextualized Late Interactions using Enhanced Reduction. In CIKM ’22: Proceedings of the 31st ACM International Conference on Information & Knowledge Management (pp. 737–747). Association for Computing Machinery (ACM). https://doi.org/10.1145/3511808.3557367
    Download: Artikel (1.18 MB)
    Project: DoSSIER (2019–2024)
  • Benchmark for Research Theme Classification of Scholarly Documents / Mendoza, O., Kusa, W., El-Ebshihy, A. M., Wu, R., Pride, D., Knoth, P., Herrmannova, D., Piroi, F., Pasi, G., & Hanbury, A. (2022). Benchmark for Research Theme Classification of Scholarly Documents. In Proceedings of the Workshop. Third Workshop on Scholarly Document Processing (pp. 253–262). Association for Computational Linguistics. https://doi.org/10.34726/4521
    Download: PDF (519 KB)
    Project: DoSSIER (2019–2024)
  • TripJudge: A Relevance Judgement Test Collection for TripClick Health Retrieval / Althammer, S., Hofstätter, S., Verberne, S., & Hanbury, A. (2022). TripJudge: A Relevance Judgement Test Collection for TripClick Health Retrieval. In CIKM ’22: Proceedings of the 31st ACM International Conference on Information & Knowledge Management (pp. 3801–3805). https://doi.org/10.1145/3511808.3557714
  • Leveraging Wikipedia Knowledge for Distant Supervision in Medical Concept Normalization / Ningtyas, A. M., El-Ebshihy, A., Herwanto, G. B., Piroi, F., & Hanbury, A. (2022). Leveraging Wikipedia Knowledge for Distant Supervision in Medical Concept Normalization. In Experimental IR Meets Multilinguality, Multimodality, and Interaction (pp. 33–47). Springer Nature Switzerland AG. https://doi.org/10.1007/978-3-031-13643-6_3
  • AI and Data Landscape in Austria / Hanbury, A. (2022, July 11). AI and Data Landscape in Austria [Presentation]. Horizon Europe – AI, Data & Robotics Consortia Building Event, United Kingdom of Great Britain and Northern Ireland (the). http://hdl.handle.net/20.500.12708/153256
  • DoSSIER at MedVidQA 2022: Text-based Approaches to Medical Video Answer Localization Problem / Kusa, W., Peikos, G., Espitia Mendoza, Ó., Hanbury, A., & Pasi, G. (2022). DoSSIER at MedVidQA 2022: Text-based Approaches to Medical Video Answer Localization Problem. In Proceedings of the 21st Workshop on Biomedical Language Processing (pp. 432–440). Association for Computational Linguistics. https://doi.org/10.18653/v1/2022.bionlp-1.43
    Download: PDF (728 KB)
    Project: DoSSIER (2019–2024)
  • Automated analysis of legal text for building regulation: the BRISE project / Hanbury, A. (2022, April 21). Automated analysis of legal text for building regulation: the BRISE project [Presentation]. HPC for digital history and public administration, Luxembourg. http://hdl.handle.net/20.500.12708/153859
    Project: VHH (2019–2023)
  • The DoSSIER project: Domain Specific Systems for Information Extraction and Retrieval / Hanbury, A. (2022, April 10). The DoSSIER project: Domain Specific Systems for Information Extraction and Retrieval [Keynote Presentation]. 1st Workshop on Augmented Intelligence for Technology-Assisted Reviews Systems: Evaluation Metrics and Protocols for eDiscovery and Systematic Review Systems (with the ECIR), Stavanger, Norway. http://hdl.handle.net/20.500.12708/153992
    Project: DoSSIER (2019–2024)
  • A Time-Optimized Content Creation Workflow for Remote Teaching / Hofstätter, S., Althammer, S., Sertkan, M., & Hanbury, A. (2022). A Time-Optimized Content Creation Workflow for Remote Teaching. In SIGCSE 2022: Proceedings of the 53rd ACM Technical Symposium on Computer Science Education (pp. 731–737). Association for Computing Machinery. https://doi.org/10.1145/3478431.3499421
  • Proceedings of the 3rd Workshop on Patent Text Mining and Semantic Technologies / Krestel, R., Aras, H., Andersson, L., Piroi, F., Hanbury, A., & Alderucci, D. (Eds.). (2022). Proceedings of the 3rd Workshop on Patent Text Mining and Semantic Technologies. https://doi.org/10.34726/3550
    Download: PDF (3.92 MB)
    Project: DoSSIER (2019–2024)
  • Automation of Citation Screening for Systematic Literature Reviews Using Neural Networks: A Replicability Study / Kusa, W., Hanbury, A., & Knoth, P. (2022). Automation of Citation Screening for Systematic Literature Reviews Using Neural Networks: A Replicability Study. In M. Hagen, S. Verberne, C. Macdonald, C. Seifert, K. Balog, K. Norvag, & V. Setty (Eds.), Advances in Information Retrieval. 44th European Conference on IR Research, ECIR 2022, Stavanger, Norway, April 10–14, 2022, Proceedings, Part I (pp. 584–598). Springer. https://doi.org/10.34726/4261
    Download: paper (283 KB)
    Project: DoSSIER (2019–2024)
  • PARM: A Paragraph Aggregation Retrieval Model for Dense Document-to-Document Retrieval / Althammer, S., Hofstätter, S., Sertkan, M., Verberne, S., & Hanbury, A. (2022). PARM: A Paragraph Aggregation Retrieval Model for Dense Document-to-Document Retrieval. In Advances in Information Retrieval (pp. 19–34). Springer. https://doi.org/10.1007/978-3-030-99736-6_2
  • 3rd Workshop on Patent Text Mining and Semantic Technologies (PatentSemTech2022) / Krestel, R., Aras, H., Andersson, L., Piroi, F., Hanbury, A., & Alderucci, D. (2022). 3rd Workshop on Patent Text Mining and Semantic Technologies (PatentSemTech2022). Association for Computing Machinery. https://doi.org/10.1145/3477495.3531702
    Project: DoSSIER (2019–2024)

2021

2020

  • Comparing Implementation Variants Of Distributed Spatial Join on Spark / Heiler, G., & Hanbury, A. (2020). Comparing Implementation Variants Of Distributed Spatial Join on Spark. In 2019 IEEE International Conference on Big Data (Big Data) (pp. 6071–6073). http://hdl.handle.net/20.500.12708/58397
  • BIAS: Transparent reporting of biomedical image analysis challenges / Maier-Hein, L., Reinke, A., Kozubek, M., Martel, A. L., Arbel, T., Eisenmann, M., Hanbury, A., Jannin, P., Müller, H., Onogur, S., Saez-Rodriguez, J., van Ginneken, B., Kopp-Schneider, A., & Landman, B. A. (2020). BIAS: Transparent reporting of biomedical image analysis challenges. Medical Image Analysis, 66(101796), 101796. https://doi.org/10.1016/j.media.2020.101796
  • An annotated fluorescence image dataset for training nuclear image segmentation methods / Kromp, F., Bozsaky, E., Rifatbegovic, F., Fischer, L., Ambros, M., Berneder, M., Weiss, T., Lazic, D., Dörr, W., Hanbury, A., Beiske, K., Ambros, P. F., Ambros, I. M., & Tashner-Mandl, S. (2020). An annotated fluorescence image dataset for training nuclear image segmentation methods. Scientific Data, 7(262). https://doi.org/10.1038/s41597-020-00608-w
  • Country-wide mobility changes observed using mobile phone data during COVID-19 pandemic / Heiler, G., Reisch, T., Hurt, J., Forghani, M., Omani, A., Hanbury, A., & Karimipour, F. (2020). Country-wide mobility changes observed using mobile phone data during COVID-19 pandemic (p. 9). arXiv. https://doi.org/10.48550/arXiv.2008.10064
  • The impact of COVID-19 on relative changes in aggregated mobility using mobile-phone data / Heiler, G., Hanbury, A., & Filzmoser, P. (2020). The impact of COVID-19 on relative changes in aggregated mobility using mobile-phone data (p. 14). arXiv. https://doi.org/10.48550/arXiv.2009.03798
  • Behavioural gender differences are increased by lock-down measures. / Reisch, T., Heiler, G., Hurt, J., Klimek, P., Hanbury, A., & Thurner, S. (2020). Behavioural gender differences are increased by lock-down measures. (p. 26). arXiv. http://hdl.handle.net/20.500.12708/141682
  • Improving Efficient Neural Ranking Models with Cross-Architecture Knowledge Distillation / Hofstätter, S., Althammer, S., Schröder, M., Sertkan, M., & Hanbury, A. (2020). Improving Efficient Neural Ranking Models with Cross-Architecture Knowledge Distillation (p. 8). arXiv. http://hdl.handle.net/20.500.12708/141680
  • Explainable AI in the medical and legal domains / Hanbury, A. (2020). Explainable AI in the medical and legal domains. International Digital Security Forum Vienna, Wien (online), Austria. http://hdl.handle.net/20.500.12708/87139
  • Open Science with Closed Data / Hanbury, A. (2020). Open Science with Closed Data. Online conference “Openness and Commercialisation: How the two can go together”, TU Delft, Delft (online), EU. http://hdl.handle.net/20.500.12708/87140
  • Corona und die Wissenschaft. Panel Diskussion. / Hanbury, A. (2020). Corona und die Wissenschaft. Panel Diskussion. 27. TU Forum: Corona und die Wissenschaft, Wien (online), Austria. http://hdl.handle.net/20.500.12708/87138
  • Die Datenwirtschaft und die Data Intelligence Offensive / Hanbury, A. (2020). Die Datenwirtschaft und die Data Intelligence Offensive. ADV Tagung 2020: Trends in der Digitalisierung, Wien, Austria. http://hdl.handle.net/20.500.12708/87137
  • Von der KI Forschung zum Produkt - Herausforderungen und Erfolge / Hanbury, A. (2020). Von der KI Forschung zum Produkt - Herausforderungen und Erfolge. Workshop: Künstliche Intelligenz in der Gesundheit, Regensburg, Germany (online), EU. http://hdl.handle.net/20.500.12708/87136
  • Supporting Systematic Reviews in Medicine / Hanbury, A. (2020). Supporting Systematic Reviews in Medicine. WOSP 2020 - 8th International Workshop on Mining Scientific Publications, Wuhan, China (online), Non-EU. http://hdl.handle.net/20.500.12708/87135
  • Medizinische Daten und künstliche Intelligenz / Hanbury, A. (2020). Medizinische Daten und künstliche Intelligenz. Webinar “Medizinische Datenintelligenz”, organised by the Research and Transfer Support office of the TU Wien, Wien (online), Austria. http://hdl.handle.net/20.500.12708/87134
  • Neural-IR-Explorer: A Content-Focused Tool to Explore Neural Re-ranking Results / Hofstätter, S., Zlabinger, M., & Hanbury, A. (2020). Neural-IR-Explorer: A Content-Focused Tool to Explore Neural Re-ranking Results. In Lecture Notes in Computer Science (pp. 459–464). Springer. https://doi.org/10.1007/978-3-030-45442-5_58
  • Local Self-Attention over Long Text for Efficient Document Retrieval / Hofstätter, S., Zamani, H., Mitra, B., Craswell, N., & Hanbury, A. (2020). Local Self-Attention over Long Text for Efficient Document Retrieval. In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval. SIGIR 2020 - 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, Xi’an, China, Non-EU. Association for Computing Machinery, New York, NY, United States. https://doi.org/10.1145/3397271.3401224
  • DSR: A Collection for the Evaluation of Graded Disease-Symptom Relations / Zlabinger, M., Hofstätter, S., Rekabsaz, N., & Hanbury, A. (2020). DSR: A Collection for the Evaluation of Graded Disease-Symptom Relations. In Lecture Notes in Computer Science (pp. 433–440). Springer Nature Switzerland AG 2021. https://doi.org/10.1007/978-3-030-45442-5_54
  • Effective Crowd-Annotation of Participants, Interventions, and Outcomes in the Text of Clinical Trial Reports / Zlabinger, M., Sabou, M., Hofstätter, S., & Hanbury, A. (2020). Effective Crowd-Annotation of Participants, Interventions, and Outcomes in the Text of Clinical Trial Reports. In T. Cohn, Y. He, & Y. Liu (Eds.), Findings of the Association for Computational Linguistics: EMNLP 2020. The Association for Computational Linguistics. https://doi.org/10.18653/v1/2020.findings-emnlp.274
  • Learning to Re-Rank with Contextualized Stopwords / Hofstätter, S., Lipani, A., Zlabinger, M., & Hanbury, A. (2020). Learning to Re-Rank with Contextualized Stopwords. In Proceedings of the 29th ACM International Conference on Information & Knowledge Management. CIKM 2020: International Conference on Information & Knowledge Management 2020, Virtual Event, Ireland, EU. https://doi.org/10.1145/3340531.3412079
  • DEXA: Supporting Non-Expert Annotators with Dynamic Examples from Experts / Zlabinger, M., Sabou, M., Hofstätter, S., Sertkan, M., & Hanbury, A. (2020). DEXA: Supporting Non-Expert Annotators with Dynamic Examples from Experts. In J. Huang & Y. Chang (Eds.), Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval. Association for Computing Machinery, New York, NY, United States. https://doi.org/10.1145/3397271.3401334
  • Fine-Grained Relevance Annotations for Multi-Task Document Ranking and Question Answering / Hofstätter, S., Zlabinger, M., Sertkan, M., Schröder, M., & Hanbury, A. (2020). Fine-Grained Relevance Annotations for Multi-Task Document Ranking and Question Answering. In Proceedings of the 29th ACM International Conference on Information & Knowledge Management. CIKM 2020: International Conference on Information & Knowledge Management 2020, Virtual Event, Ireland, EU. Association for Computing Machinery. https://doi.org/10.1145/3340531.3412878
  • Interpretable & time-budget-constrained contextualization for re-ranking / Hofstätter, S., Zlabinger, M., & Hanbury, A. (2020). Interpretable & time-budget-constrained contextualization for re-ranking. In ECAI 2020 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain - Including 10th Conference on Prestigious Applications of Artificial Intelligence (PAIS 2020) (pp. 1–8). IOS Press. http://hdl.handle.net/20.500.12708/55598

2019

2018

  • Evaluation-as-a-Service for the Computational Sciences: Overview and Outlook / Hopfgartner, F., Hanbury, A., & Müller, H. (2018). Evaluation-as-a-Service for the Computational Sciences: Overview and Outlook. ACM Journal of Data and Information Quality, 10(4), 1–32. https://doi.org/10.1145/3239570
  • Why rankings of biomedical image analysis competitions should be interpreted with care / Maier-Hein, L., Eisenmann, M., Reinke, A., Onogur, S., Stankovic, M., Scholz, P., Arbel, T., Bogunovic, H., Carass, A., Feldmann, C., F. Frangi, A., Full, P. M., van Ginneken, B., Hanbury, A., Honauer, K., Kozubek, M., Landman, B. A., März, K., & Kopp-Schneider, A. (2018). Why rankings of biomedical image analysis competitions should be interpreted with care. Nature Communications, 9(5217). https://doi.org/10.1038/s41467-018-07619-7
  • A systematic approach to normalization in probabilistic models / Lipani, A., Roelleke, T., Lupu, M., & Hanbury, A. (2018). A systematic approach to normalization in probabilistic models. Information Retrieval, 21(6), 565–596. https://doi.org/10.1007/s10791-018-9334-1
  • Contextual local primitives for binary patent image retrieval / Bhatti, N., Hanbury, A., & Stottinger, J. (2018). Contextual local primitives for binary patent image retrieval. Multimedia Tools and Applications, 77(7), 9111–9151. https://doi.org/10.1007/s11042-017-4808-5
  • Word Relatedness from Word Embedding in Information Retrieval / Hanbury, A. (2018). Word Relatedness from Word Embedding in Information Retrieval. Forum for Information Retrieval Evaluation (FIRE), Virtual Conference, International. http://hdl.handle.net/20.500.12708/87159
  • Credibility of sources, content, and algorithms / Hanbury, A. (2018). Credibility of sources, content, and algorithms. Fake News and other AI Challenges for the News Media in the 21st Century, panel member for the discussion on “Solving Ethical & Technical Challenges of Fake News,” Wien, Austria. http://hdl.handle.net/20.500.12708/87158
  • Data Intelligence und Recht / Hanbury, A. (2018). Data Intelligence und Recht. Working group “Perspektiven der Rechtsetzung” of the Directorate of the Austrian Parliament, Wien, Austria. http://hdl.handle.net/20.500.12708/87157
  • Maschinen als Begleiter: Wie digitale Assistenten zum Alltag werden / Hanbury, A. (2018). Maschinen als Begleiter: Wie digitale Assistenten zum Alltag werden. Austrian Press Agency Digital Business Trends event, Wien, Austria. http://hdl.handle.net/20.500.12708/87156
  • Lexical and Statistical Semantics in Professional Search / Hanbury, A. (2018). Lexical and Statistical Semantics in Professional Search. Semantics 2018 conference, Wien, Austria. http://hdl.handle.net/20.500.12708/87155
  • Sentiment Analysis in Finance / Hanbury, A. (2018). Sentiment Analysis in Finance. VISS 2018 - Vienna International Summer School on Machine Learning Methods and Data Analytics in Risk and Insurance, Wien, Austria. http://hdl.handle.net/20.500.12708/87154
  • Word Embedding and Applications / Hanbury, A. (2018). Word Embedding and Applications. U Wien Inter-Faculty Research Centre on Computational Complex Systems Meeting: Drawing Insights from Complex Data, Wien, Austria. http://hdl.handle.net/20.500.12708/87153
  • Unstructured Information in Data Science: Word Relatedness from Word Embedding / Hanbury, A. (2018). Unstructured Information in Data Science: Word Relatedness from Word Embedding. Data Science Society Meet-Up, Vienna, Austria. http://hdl.handle.net/20.500.12708/87152
  • Word relatedness from Word Embedding in text analysis and information retrieval / Hanbury, A. (2018). Word relatedness from Word Embedding in text analysis and information retrieval. TU Berlin, Berlin, Germany, EU. http://hdl.handle.net/20.500.12708/87151
  • A New Framework for Multidimensional Evaluation of Search Engines / Palotti, J., Zuccon, G., & Hanbury, A. (2018). A New Framework for Multidimensional Evaluation of Search Engines. In Proc. 27th ACM International Conference on Information and Knowledge Management (CIKM 2018) (pp. 1699–1702). ACM Digital Library. http://hdl.handle.net/20.500.12708/57730
  • Medical Entity Corpus with PICO elements and Sentiment Analysis / Zlabinger, M., Andersson, L., Hanbury, A., Andersson, M., Quasnik, V., & Brassey, J. (2018). Medical Entity Corpus with PICO elements and Sentiment Analysis. In LREC 2018, Eleventh International Conference on Language Resources and Evaluation (pp. 292–296). International Conference on Language Resources and Evaluation. http://hdl.handle.net/20.500.12708/57568

2017

  • Toward Optimized Multimodal Concept Indexing / Rekabsaz, N., Bierig, R., Lupu, M., & Hanbury, A. (2017). Toward Optimized Multimodal Concept Indexing. In A. M. Pinto & J. Cardoso (Eds.), Transactions on Computational Collective Intelligence XXVI (Vol. 10190, pp. 144–161). Springer. https://doi.org/10.1007/978-3-319-59268-8_7
  • Volatility Prediction using Financial Disclosures Sentiments with Word Embedding-based IR Models / Rekabsaz, N., Lupu, M., Baklanov, A., Dür, A., Andersson, L., & Hanbury, A. (2017). Volatility Prediction using Financial Disclosures Sentiments with            Word Embedding-based IR Models. In Proceedings of the 55th Annual Meeting of the Association for          Computational Linguistics (Volume 1: Long Papers). Association for Computational Linguistics, Vancouver, Canada, Non-EU. Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics. https://doi.org/10.18653/v1/p17-1157
  • Extracting the Population, Intervention, Comparison and Sentiment from Randomized Controlled Trials. / Zlabinger, M., Andersson, L., Brassey, J., & Hanbury, A. (2017). Extracting the Population, Intervention, Comparison and Sentiment from Randomized Controlled Trials. In A. Ugon, D. Karlsson, G. O. Klein, & A. Moen (Eds.), Building Continents of Knowledge in Oceans of Data: The Future of Co-Created eHealth – Proceedings of MIE2018 (Vol. 247, pp. 146–150). IOS Press. https://doi.org/10.3233/978-1-61499-852-5-146
  • The Portability of Three Types of Text Mining Techniques into the Patent Text Genre / Andersson, L., Hanbury, A., & Rauber, A. (2017). The Portability of Three Types of Text Mining Techniques into the Patent Text Genre. In M. Lupu, K. Mayer, N. Kando, & A. Trippe (Eds.), Current Challenges in Patent Information Retrieval (pp. 241–280). Springer. http://hdl.handle.net/20.500.12708/24332
  • Message ranking in a factory setting using context and user preference / Taha, A. A., Piroi, F., Hanbury, A., Tropper, T., Mutzl, T., & Shehata, H. (2017). Message ranking in a factory setting using context and user preference. In 2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA). IEEE. https://doi.org/10.1109/etfa.2017.8247708
  • Word Embedding Causes Topic Shifting; Exploit Global Context! / Rekabsaz, N., Lupu, M., Hanbury, A., & Zamani, H. (2017). Word Embedding Causes Topic Shifting; Exploit Global Context! In Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM SIGIR Conference on Research and Development in Information Retrieval, Shinjuku , Tokyo, Japan, Non-EU. ACM. https://doi.org/10.1145/3077136.3080733
  • Visual Pool / Lipani, A., Lupu, M., & Hanbury, A. (2017). Visual Pool. In Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM. https://doi.org/10.1145/3077136.3084146
  • Fixed budget pooling strategies based on fusion methods / Lipani, A., Lupu, M., Palotti, J., Zuccon, G., & Hanbury, A. (2017). Fixed budget pooling strategies based on fusion methods. In Proceedings of the Symposium on Applied Computing. ACM. https://doi.org/10.1145/3019612.3019692
  • Fixed-Cost Pooling Strategies Based on IR Evaluation Measures / Lipani, A., Palotti, J., Lupu, M., Piroi, F., Zuccon, G., & Hanbury, A. (2017). Fixed-Cost Pooling Strategies Based on IR Evaluation Measures. In Lecture Notes in Computer Science (pp. 357–368). Springer Nature Switzerland AG 2021. https://doi.org/10.1007/978-3-319-56608-5_28
  • Finding duplicate images in biology papers / Zlabinger, M., & Hanbury, A. (2017). Finding duplicate images in biology papers. In Proceedings of the Symposium on Applied Computing. Symposium on Applied Computing (SAC), Villa Olmo, Como, Italy, Austria. SAC ’17 Proceedings of the Symposium on Applied Computing. https://doi.org/10.1145/3019612.3019875
  • Exploration of a Threshold for Similarity Based on Uncertainty in Word Embedding / Rekabsaz, N., Lupu, M., Hanbury, A., & Zuccon, G. (2017). Exploration of a Threshold for Similarity Based on Uncertainty in Word Embedding. In Lecture Notes in Computer Science (pp. 396–409). Springer, Cham. https://doi.org/10.1007/978-3-319-56608-5_31
  • Does Online Evaluation Correspond to Offline Evaluation in Query Auto Completion? / Bampoulidis, A., Palotti, J., Lupu, M., Brassey, J., & Hanbury, A. (2017). Does Online Evaluation Correspond to Offline Evaluation in Query Auto Completion? In Advances in Information Retrieval (pp. 713–719). Springer. http://hdl.handle.net/20.500.12708/56925
  • Automatic query expansion for patent passage retrieval using paradigmatic and syntagmatic information / Andersson, L., Rekabsaz, N., & Hanbury, A. (2017). Automatic query expansion for patent passage retrieval using paradigmatic and syntagmatic information. In The first WiNLP Workshop co-located with with the Annual Meeting of the Association for Computational Linguistics (ACL 2017), Vancouver (p. 4). http://hdl.handle.net/20.500.12708/57020
  • Cloud-Based Benchmarking of Medical Image Analysis / Hanbury, A., Müller, H., & Langs, G. (Eds.). (2017). Cloud-Based Benchmarking of Medical Image Analysis. Springer International Publishing. http://hdl.handle.net/20.500.12708/24397

2016

  • Cloud-Based Evaluation of Anatomical Structure Segmentation and Landmark Detection Algorithms: VISCERAL Anatomy Benchmarks / Jimenez del Toro, O. A., Müller, H., Krenn, M., Grünberg, K., Taha, A. A., Winterstein, M., Eggel, I., Foncubierta-Rodríguez, A., Goksel, O., Jakab, A., Kontokotsios, G., Langs, G., Menze, B. H., Fernandez, T. S., Schaer, R., Walleyo, A., Weber, M.-A., Dicente Cid, Y., Gass, T., & Hanbury, A. (2016). Cloud-Based Evaluation of Anatomical Structure Segmentation and Landmark Detection Algorithms: VISCERAL Anatomy Benchmarks. IEEE Transactions on Medical Imaging, 35(11), 2459–2475. https://doi.org/10.1109/tmi.2016.2578680
  • Making sense of big data in health research: Towards an EU action plan / Auffray, C., Balling, R., Barroso, I., Bencze, L., Benson, M., Bergeron, J., Bernal-Delgado, E., Blomberg, N., Bock, C., Conesa, A., Del Signore, S., DELOGNE, C., Devilee, P., Di Meglio, A., Eijkemans, M., Flicek, P., Graf, N., Grimm, V., Hanbury, A., & Zanetti, G. (2016). Making sense of big data in health research: Towards an EU action plan. Genome Medicine, 8, Article 71. https://doi.org/10.1186/s13073-016-0323-y
  • Uncertainty in Neural Network Word Embedding Exploration of Threshold for Similarity / Rekabsaz, N., Lupu, M., & Hanbury, A. (2016). Uncertainty in Neural Network Word Embedding Exploration of Threshold for Similarity. Neu-IR: The SIGIR 2016 Workshop on Neural Information Retrieval, Pisa, EU. http://hdl.handle.net/20.500.12708/86458
  • Interactive exploration of healthcare queries / Bampoulidis, A., Palotti, J., Brassey, J., Lupu, M., Metallidis, S., & Hanbury, A. (2016). Interactive exploration of healthcare queries. In 2016 14th International Workshop on Content-Based Multimedia Indexing (CBMI). 14th International Workshop on Content-based Multimedia Indexing, Bukarest, Rumänien, EU. IEEE. https://doi.org/10.1109/cbmi.2016.7500275
  • Toward Incorporation of Relevant Documents in word2vec / Rekabsaz, N., Lupu, M., Hanbury, A., & Bhaskar, M. (2016). Toward Incorporation of Relevant Documents in word2vec. In Neu-IR Workshop at the ACM Conference on Research and Development in Information Retrieval. Neu-IR Workshop, Pisa, EU. http://hdl.handle.net/20.500.12708/57150
  • Machine Learning Framework incorporating Expert Knowledge in Tissue Image Annotation / Kromp, F., Ambros, P., Ambros, I., Weiss, T., & Hanbury, A. (2016). Machine Learning Framework incorporating Expert Knowledge in Tissue Image Annotation. In Proceedings of the ICPR 2016 (p. 5). IEEE. http://hdl.handle.net/20.500.12708/56894
  • Assessors Agreement: A Case Study Across Assessor Type, Payment Levels, Query Variations and Relevance Dimensions / Palotti, J., Zuccon, G., Bernhardt, J., Hanbury, A., & Goeuriot, L. (2016). Assessors Agreement: A Case Study Across Assessor Type, Payment Levels, Query Variations and Relevance Dimensions. In Lecture Notes in Computer Science (pp. 40–53). Springer. https://doi.org/10.1007/978-3-319-44564-9_4
  • When is the Time Ripe for Natural Language Processing for Patent Passage Retrieval? / Andersson, L., Lupu, M., Palotti, J., Hanbury, A., & Rauber, A. (2016). When is the Time Ripe for Natural Language Processing for Patent Passage Retrieval? In Proceedings of the 25th ACM International on Conference on Information and Knowledge Management. Acm Dl. https://doi.org/10.1145/2983323.2983858
  • Generalizing Translation Models in the Probabilistic Relevance Framework / Rekabsaz, N., Lupu, M., Hanbury, A., & Zuccon, G. (2016). Generalizing Translation Models in the Probabilistic Relevance Framework. In Proceedings of the 25th ACM International on Conference on Information and Knowledge Management. 25th ACM International on Conference on Information and Knowledge Management (CIKM), Indianapolis, Indiana, USA, Non-EU. ACM. https://doi.org/10.1145/2983323.2983833
  • The Solitude of Relevant Documents in the Pool / Lipani, A., Lupu, M., Kanoulas, E., & Hanbury, A. (2016). The Solitude of Relevant Documents in the Pool. In Proceedings of the 2016 ACM on International Conference on the Theory of Information Retrieval (pp. 1989–1992). ACM. http://hdl.handle.net/20.500.12708/56640
  • The Impact of Fixed-Cost Pooling Strategies on Test Collection Bias / Lipani, A., Zuccon, G., Lupu, M., Koopman, B., & Hanbury, A. (2016). The Impact of Fixed-Cost Pooling Strategies on Test Collection Bias. In Proceedings of the 2016 ACM on International Conference on the Theory of Information Retrieval (pp. 105–108). ACM. http://hdl.handle.net/20.500.12708/56639
  • The Curious Incidence of Bias Corrections in the Pool / Lipani, A., Lupu, M., & Hanbury, A. (2016). The Curious Incidence of Bias Corrections in the Pool. In Lecture Notes in Computer Science (pp. 267–279). Springer. https://doi.org/10.1007/978-3-319-30671-1_20
  • Standard Test Collection for English-Persian Cross-Lingual Word Sense Disambiguation / Rekabsaz, N., Sabetghadam, S., Andersson, L., Lupu, M., & Hanbury, A. (2016). Standard Test Collection for English-Persian Cross-Lingual Word Sense Disambiguation. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016). Tenth International Conference on Language Resources and Evaluation (LREC 2016), Portoroz, Slovenia, EU. European Language Resources Association (ELRA). http://hdl.handle.net/20.500.12708/56635
  • Ranking Health Web Pages with Relevance and Understandability / Palotti, J., Goeuriot, L., Zuccon, G., & Hanbury, A. (2016). Ranking Health Web Pages with Relevance and Understandability. In Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval. ACM, Austria. ACM. https://doi.org/10.1145/2911451.2914741
  • Query Variations and their Effect on Comparing Information Retrieval Systems / Zuccon, G., Palotti, J., & Hanbury, A. (2016). Query Variations and their Effect on Comparing Information Retrieval Systems. In Proceedings of the 25th ACM International on Conference on Information and Knowledge Management. ACM. https://doi.org/10.1145/2983323.2983723

2015

  • DASyR(IR) - Document Analysis System for Systematic Reviews (in Information Retrieval) / Piroi, F., Lipani, A., Lupu, M., & Hanbury, A. (2015). DASyR(IR) - Document Analysis System for Systematic Reviews (in Information Retrieval). In 13th International Conference on Document Analysis and Recognition (ICDAR), 2015 (pp. 591–595). IEEE Xplore. http://hdl.handle.net/20.500.12708/56327
  • Metrics for evaluating 3D medical image segmentation: analysis, selection, and tool / Taha, A. A., & Hanbury, A. (2015). Metrics for evaluating 3D medical image segmentation: analysis, selection, and tool. BMC Medical Imaging. https://doi.org/10.1186/s12880-015-0068-x
    Download: PDF (2.17 MB)
  • A Researcher's View on (Big) Data Analytics in Austria Results from an Online Survey / Bierig, R., Hanbury, A., Piroi, F., Haas, M., Berger, H., Lupu, M., & Dittenbach, M. (2015). A Researcher’s View on (Big) Data Analytics in Austria Results from an Online Survey. In M. Helfert, A. Holzinger, O. Belo, & C. Francalanci (Eds.), Communications in Computer and Information Science (pp. 45–61). Springer International Publishing. https://doi.org/10.1007/978-3-319-25936-9_4
  • An Efficient Algorithm for Calculating the Exact Hausdorff Distance / Taha, A. A., & Hanbury, A. (2015). An Efficient Algorithm for Calculating the Exact Hausdorff Distance. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37(11), 2153–2163. https://doi.org/10.1109/tpami.2015.2408351
  • Toward Optimized Multimodal Concept Indexing / Rekabsaz, N., Bierig, R., Lupu, M., & Hanbury, A. (2015). Toward Optimized Multimodal Concept Indexing. In J. Cardoso, F. Guerra, G.-J. Houben, A. M. Pinto, & Y. Velegrakis (Eds.), Semantic Keyword-based Search on Structured Data Sources: First COST Action IC1302 International KEYSTONE Conference, IKC 2015, Coimbra, Portugal, September 8-9, 2015. Revised Selected Papers (pp. 141–152). Springer. https://doi.org/10.1007/978-3-319-27932-9_13
  • On the use of statistical semantics for metadata-based social image retrieval / Rekabsaz, N., Bierig, R., Ionescu, B., Hanbury, A., & Lupu, M. (2015). On the use of statistical semantics for metadata-based social image retrieval. In 2015 13th International Workshop on Content-Based Multimedia Indexing (CBMI). 13th International Workshop on Content-Based Multimedia Indexing (CBMI 2015), Prague, Czech Republic, EU. IEEE. https://doi.org/10.1109/cbmi.2015.7153634
  • Detecting Risks in the Banking System by Sentiment Analysis / Nopp, C., & Hanbury, A. (2015). Detecting Risks in the Banking System by Sentiment Analysis. In Proceedings of the EMNLP 2015 (pp. 591–600). The Association for Computational Linguistics. http://hdl.handle.net/20.500.12708/56271
  • Splitting Water / Lipani, A., Lupu, M., & Hanbury, A. (2015). Splitting Water. In Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM. https://doi.org/10.1145/2766462.2767749
  • An Initial Analytical Exploration of Retrievability / Lipani, A., Lupu, M., Aizawa, A., & Hanbury, A. (2015). An Initial Analytical Exploration of Retrievability. In Proceedings of the 2015 International Conference on The Theory of Information Retrieval. ACM, Austria. ACM. https://doi.org/10.1145/2808194.2809495
  • Verboseness Fission for BM25 Document Length Normalization / Lipani, A., Lupu, M., Hanbury, A., & Aizawa, A. (2015). Verboseness Fission for BM25 Document Length Normalization. In Proceedings of the 2015 International Conference on The Theory of Information Retrieval. ACM. https://doi.org/10.1145/2808194.2809486
  • Using Health Statistics to Improve Medical and Health Search / Sierek, T., & Hanbury, A. (2015). Using Health Statistics to Improve Medical and Health Search. In Experimental IR Meets Multilinguality, Multimodality, and Interaction (pp. 287–292). Springer. http://hdl.handle.net/20.500.12708/55929

2014

  • Domain Specific Search / Lupu, M., Hanbury, A., & Salampasis, M. (2014). Domain Specific Search. In G. Paltoglou, F. Loizides, & P. Hansen (Eds.), Professional Search in the Modern World (pp. 96–117). Springer LNCS. https://doi.org/10.1007/978-3-319-12511-4_6
  • Visual Methods for Analyzing Probabilistic Classification Data / Alsallakh, B., Hanbury, A., Hauser, H., Miksch, S., & Rauber, A. (2014). Visual Methods for Analyzing Probabilistic Classification Data. IEEE Transactions on Visualization and Computer Graphics, 20(12), 1703–1712. https://doi.org/10.1109/tvcg.2014.2346660
  • Systematic skin segmentation: merging spatial and non-spatial data / Khan, R., Hanbury, A., Sablatnig, R., Stöttinger, J., Khan, F. A., & Khan, F. A. (2014). Systematic skin segmentation: merging spatial and non-spatial data. Multimedia Tools and Applications, 69(3), 717–741. https://doi.org/10.1007/s11042-012-1124-y
  • A Glimpse into the State and Future of (Big) Data Analytics in Austria / Bierig, R., Hanbury, A., Haas, M., Piroi, F., Berger, H., Lupu, M., & Dittenbach, M. (2014). A Glimpse into the State and Future of (Big) Data Analytics in Austria. In M. Helfert, A. Holzinger, O. Belo, & C. Francalanci (Eds.), Proceedings of 3rd International Conference on Data Management Technologies and Applications (pp. 178–188). ScitePress. https://doi.org/10.5220/0004999101780188
  • TUW @ Retrieving Diverse Social Images Task 2014 / Palotti, J., Rekabsaz, N., Lupu, M., & Hanbury, A. (2014). TUW @ Retrieving Diverse Social Images Task 2014. In Working Notes Proceedings of the MediaEval 2014 Workshop. MediaEval Benchmarking Initiative for Multimedia Evaluation, Barcelona, ES, EU. CEUR-WS. http://hdl.handle.net/20.500.12708/55380
  • Insight to Hyponymy Lexical Relation Extraction in the Patent Genre Versus Other Text Genres / Andersson, L., Lupu, M., Palotti, J., Piroi, F., Hanbury, A., & Rauber, A. (2014). Insight to Hyponymy Lexical Relation Extraction in the Patent Genre Versus Other Text Genres. In Patent Mining and Its Applications. First International Workshop on Patent Mining and Its Applications (IPaMin 2014), Hildesheim, Germany, EU. CEUR Workshop Proceedings. http://hdl.handle.net/20.500.12708/55377
  • A formal method for selecting evaluation metrics for image segmentation / Taha, A. A., Hanbury, A., & del Toro, O. A. J. (2014). A formal method for selecting evaluation metrics for image segmentation. In 2014 IEEE International Conference on Image Processing (ICIP). IEEE ICIP Proceedings, Austria. IEEE. https://doi.org/10.1109/icip.2014.7025187
  • User intent behind medical queries / Palotti, J. R. M., Stefanov, V., & Hanbury, A. (2014). User intent behind medical queries. In Proceedings of the 5th Information Interaction in Context Symposium. Information Interaction in Context conference, Regensburg, EU. ACM. https://doi.org/10.1145/2637002.2637043
  • A System Framework for Concept- and Credibility-Based Multimedia Retrieval / Bierig, R., Serban, C., Siriteanu, A., Lupu, M., & Hanbury, A. (2014). A System Framework for Concept- and Credibility-Based Multimedia Retrieval. In Proceedings of International Conference on Multimedia Retrieval. International Conference on Multimedia Retrieval (ICMR 2014), Glasgow, EU. ACM Press. https://doi.org/10.1145/2578726.2582624
  • Extracting Nanopublications from IR Papers / Lipani, A., Piroi, F., Andersson, L., & Hanbury, A. (2014). Extracting Nanopublications from IR Papers. In Lecture Notes in Computer Science (pp. 53–62). Springer. https://doi.org/10.1007/978-3-319-12979-2_5
  • An Information Retrieval Ontology for Information Retrieval Nanopublications / Lipani, A., Piroi, F., Andersson, L., & Hanbury, A. (2014). An Information Retrieval Ontology for Information Retrieval Nanopublications. In Lecture Notes in Computer Science (pp. 44–49). Springer Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-319-11382-1_5
  • Guest editorial: Special issue on information retrieval in the intellectual property domain / Hanbury, A., Lupu, M., Kando, N., Diallo, B., & Adams, S. (2014). Guest editorial: Special issue on information retrieval in the intellectual property domain. In Information Retrieval (pp. 407–411). Springer. https://doi.org/10.1007/s10791-014-9245-8
  • Test Data and Results of the Automatic Metric Selection Method / Taha Abdel, A., Hanbury, A., & Jimenez del Toro, O. A. (2014). Test Data and Results of the Automatic Metric Selection Method. http://hdl.handle.net/20.500.12708/38055
  • Information Access Evaluation. Multilinguality, Multimodality, and Interaction / Information Access Evaluation. Multilinguality, Multimodality, and Interaction. (2014). In E. Kanoulas, M. Lupu, P. Clough, M. Sanderson, M. Hall, A. Hanbury, & E. Toms (Eds.), Lecture Notes in Computer Science. Springer. https://doi.org/10.1007/978-3-319-11382-1

2013

  • Evaluating Flowchart Recognition for Patent Retrieval / Lupu, M., Piroi, F., & Hanbury, A. (2013). Evaluating Flowchart Recognition for Patent Retrieval. In The Fifth International Workshop on Evaluating Information Access. The Fifth International Workshop on Evaluating Information Access, Tokyo, Japan, Non-EU. http://hdl.handle.net/20.500.12708/54624
  • Toward a Model of Domain-Specific Search / Hanbury, A., & Lupu, M. (2013). Toward a Model of Domain-Specific Search. In Open Research Areas In Information Retrieval. Open Research Areas In Information Retrieval, Lisbon, Portugal, EU. http://hdl.handle.net/20.500.12708/54625
  • Exploring patent passage retrieval using nouns phrases / Andersson, L., Mahdabi, P., Hanbury, A., & Rauber, A. (2013). Exploring patent passage retrieval using nouns phrases. Proceeding of the 35th European conference on Advances in Information Retrieval (ECIR’13), Berlin, Heidelberg,, EU. http://hdl.handle.net/20.500.12708/86543
  • Domain Adaptation of General Natural Language Processing Tools for a Patent Claim Visualization System / Andersson, L., Lupu, M., & Hanbury, A. (2013). Domain Adaptation of General Natural Language Processing Tools for a Patent Claim Visualization System. In Proceedings of Multidisciplinary Information Retrieval, Berlin Heidelberg, EU. http://hdl.handle.net/20.500.12708/86542
  • Integrating IR Technologies for Professional Search / Salampasis, M., Fuhr, N., Hanbury, A., Lupu, M., Larsen, B., & Strindberg, H. (2013). Integrating IR Technologies for Professional Search. In Lecture Notes in Computer Science (pp. 882–885). Springer LNCS. https://doi.org/10.1007/978-3-642-36973-5_108
  • Overview of CLEF-IP 2013 Lab - Information Retrieval in the Patent Domain. / Piroi, F., Lupu, M., & Hanbury, A. (2013). Overview of CLEF-IP 2013 Lab - Information Retrieval in the Patent Domain. In Lecture Notes in Computer Science (pp. 232–249). Springer. https://doi.org/10.1007/978-3-642-40802-1_25
    Project: PROMISE (2011–2013)
  • A Formative Evaluation of a Comprehensive Search System for Medical Professionals / Stefanov, V., Sachs, A., Kritz, M., Samwald, M., Gschwandtner, M., & Hanbury, A. (2013). A Formative Evaluation of a Comprehensive Search System for Medical Professionals. In P. Forner, H. Müller, R. Paredes, P. Rosso, & B. Stein (Eds.), Lecture Notes in Computer Science (pp. 81–92). Springer Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-642-40802-1_10
  • Patent Retrieval / Patent Retrieval. (2013). In M. Lupu & A. Hanbury (Eds.), Foundations and Trends® in Information Retrieval (p. 97). Now Publishers. https://doi.org/10.1561/1500000027

2012

  • Sparse Color Interest Points for Image Retrieval and Object Categorization / Stöttinger, J., Hanbury, A., Sebe, N., & Gevers, T. (2012). Sparse Color Interest Points for Image Retrieval and Object Categorization. IEEE Transactions on Image Processing, 21(5), 2681–2692. https://doi.org/10.1109/tip.2012.2186143
  • Color based skin classification / Khan, R., Hanbury, A., Stöttinger, J., & Bais, A. (2012). Color based skin classification. Pattern Recognition Letters, 33(2), 157–163. https://doi.org/10.1016/j.patrec.2011.09.032
  • Systematic skin segmentation: merging spatial and non-spatial data / Khan, R., Hanbury, A., Sablatnig, R., Stöttinger, J., Khan, F. A., & Khan, F. A. (2012). Systematic skin segmentation: merging spatial and non-spatial data. Multimedia Tools and Applications, 69(3), 717–741. https://doi.org/10.1007/s11042-012-1124-y
  • PROMISE retreat report prospects and opportunities for information access evaluation / Ferro, N., Berendsen, R., Hanbury, A., Lupu, M., Petras, V., de Rijke, M., & Silvello, G. (2012). PROMISE retreat report prospects and opportunities for information access evaluation. ACM SIGIR Forum, 46(2), 60–84. https://doi.org/10.1145/2422256.2422265
  • Report on the CLEF-IP 2012 Experiments: Exploring Passage Retrieval with the PIPExtractor / Andersson, L., Mahdabi, P., Rauber, A., & Hanbury, A. (2012). Report on the CLEF-IP 2012 Experiments: Exploring Passage Retrieval with the PIPExtractor. In Proceeding of the of the Conference and Labs of the Evaluation Forum (CLEF2012), Pisa, EU. http://hdl.handle.net/20.500.12708/86544
  • Patent images - a glass-encased tool / Lupu, M., Mörzinger, R., Schleser, T., Schuster, R., Piroi, F., & Hanbury, A. (2012). Patent images - a glass-encased tool. In Proceedings of the 12th International Conference on Knowledge Management and Knowledge Technologies - i-KNOW ’12. ACM. https://doi.org/10.1145/2362456.2362477
  • Effects of Language and Topic Size in Patent IR: An Empirical Study / Piroi, F., Lupu, M., & Hanbury, A. (2012). Effects of Language and Topic Size in Patent IR: An Empirical Study. In Information Access Evaluation. Multilinguality, Multimodality, and Visual Analytics (pp. 54–66). Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-642-33247-0_7
    Projects: IMPEx (2012–2015) / PROMISE (2011–2013)
  • Bringing the Algorithms to the Data: Cloud-based Benchmarking for Medical Image Analysis / Hanbury, A., Müller, H., Langs, G., Weber, M.-A., Menze, B., & Salas, T. (2012). Bringing the Algorithms to the Data: Cloud-based Benchmarking for Medical Image Analysis. In Information Access Evaluation. Multilinguality, Multimodality, and Visual Analytics (pp. 24–29). http://hdl.handle.net/20.500.12708/54442
  • Robust camera self-calibration from monocular images of Manhattan worlds / Wildenauer, H., & Hanbury, A. (2012). Robust camera self-calibration from monocular images of Manhattan worlds. In 2012 IEEE Conference on Computer Vision and Pattern Recognition. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Providence, RI, USA, Non-EU. https://doi.org/10.1109/cvpr.2012.6248008

2011

  • Local Primitive Histograms for Patent Binary Image Retrieval / Bhatti, N., & Hanbury, A. (2011). Local Primitive Histograms for Patent Binary Image Retrieval. In 9th IAPR International Workshop on Graphics RECognition (GREC). 9th IAPR International Workshop on Graphics RECognition (GREC), Seoul, Südkorea, Non-EU. http://hdl.handle.net/20.500.12708/53899
  • Harnessing the Scientific Data Produced by the Experimental Evaluation Search Engines and Information Access Systems / Ferro, N., Hanbury, A., Müller, H., & Santucci, G. (2011). Harnessing the Scientific Data Produced by the Experimental Evaluation Search Engines and Information Access Systems. Procedia Computer Science, 4, 740–749. https://doi.org/10.1016/j.procs.2011.04.078
    Project: PROMISE (2011–2013)
  • An open, trustworthy and multilingual search engine for medical practitioners / Samwald, M., Kritz, M., Gschwandtner, M., Stefanov, V., & Hanbury, A. (2011). An open, trustworthy and multilingual search engine for medical practitioners. 23rd International Conference of the European Federation for Medical Informatics (MIE2011), Oslo, Norwegen, Non-EU. http://hdl.handle.net/20.500.12708/85232
    Project: KHRESMOI (2011–2014)
  • Report on the CLEF-IP 2011 Experiments: Exploring Patent Summarisation / Mahdabi, P., Andersson, L., Hanbury, A., & Crestani, F. (2011). Report on the CLEF-IP 2011 Experiments: Exploring Patent Summarisation. In Proceeding of the of the Conference and Labs of the Evaluation Forum (CLEF2011), Pisa, EU. http://hdl.handle.net/20.500.12708/86545
  • Towards an open, trustworthy and multilingual search engine for medical practitioners: News from the European Khresmoi project / Samwald, M., Kritz, M., Gschwandtner, M., Stefanov, V., & Hanbury, A. (2011). Towards an open, trustworthy and multilingual search engine for medical practitioners: News from the European Khresmoi project. In G. Schreier, D. Hayn, & E. Ammenwerth (Eds.), eHealth2011: Health Informatics meets eHealth - von der Wissenschaft zur Anwendung und zurück Grenzen überwinden - Continuity of Care. OCG. http://hdl.handle.net/20.500.12708/54575
  • Affective Computing for Wearable Diary and Lifelogging Systems: An Overview / Machajdik, J., Hanbury, A., Garz, A., & Sablatnig, R. (2011). Affective Computing for Wearable Diary and Lifelogging Systems: An Overview. In Machine Vision - Research for High Quality Processes and Products - 35th Workshop of the Austrian Association for Pattern Recognition. 35th Workshop of the Austrian Association for Pattern Recognition, Graz, Austria. http://hdl.handle.net/20.500.12708/54003
  • Providing feedback on emotional experiences and decision making / Machajdik, J., Stöttinger, J., Danelova, E., Pongratz, M., Kavicky, L., Valenti, R., & Hanbury, A. (2011). Providing feedback on emotional experiences and decision making. In IEEE Africon ’11. AFRICON 2011, Livingstone, Sambia, Non-EU. IEEE. https://doi.org/10.1109/afrcon.2011.6072130
  • Detection and Classification of Local Primitives in Line Drawings / Bhatti, N., & Hanbury, A. (2011). Detection and Classification of Local Primitives in Line Drawings. In Machine Vision - Research for High Quality Processes and Products - 35th Workshop of the Austrian Association for Pattern Recognition. 35th Workshop of the Austrian Association for Pattern Recognition, Graz, Austria. http://hdl.handle.net/20.500.12708/53896
  • Granulometry based Detection of Junction and End Points in Patent Drawings / Bhatti, N., & Hanbury, A. (2011). Granulometry based Detection of Junction and End Points in Patent Drawings. In Proceedings of the 7th International Symposium on Image and Signal Processing and Analysis (ISPA 2011) (pp. 307–312). IEEE. http://hdl.handle.net/20.500.12708/53879
  • Morphology Based Spatial Relationships between Local Primitives in Line Drawings / Bhatti, N. A., & Hanbury, A. (2011). Morphology Based Spatial Relationships between Local Primitives in Line Drawings. In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications (pp. 165–172). Lecture Notes on Computer Science. https://doi.org/10.1007/978-3-642-25085-9_19
  • Classifying Patent Images / Mörzinger, R., Horti, A., Thallinger, G., Bhatti, N., & Hanbury, A. (2011). Classifying Patent Images. In CLEF (Notebook Papers/Labs/Workshop). Conference on Multilingual and Multimodal Information Access Evaluation (CLEF 2011), Amsterdam, Niederlande, EU. http://hdl.handle.net/20.500.12708/53721
  • Systematic Evaluation of Spatio-Temporal Features on Comparative Video Challenges / Stöttinger, J., Goras, B. T., Pönitz, T., Sebe, N., Hanbury, A., & Gevers, T. (2011). Systematic Evaluation of Spatio-Temporal Features on Comparative Video Challenges. In R. Koch & F. Huang (Eds.), Computer Vision – ACCV 2010 Workshops (pp. 349–358). Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-642-22822-3_35
  • 4th international workshop on patent information retrieval (PaIR'11) / Lupu, M., Hanbury, A., & Rauber, A. (2011). 4th international workshop on patent information retrieval (PaIR’11). In Proceedings of the 20th ACM international conference on Information and knowledge management - CIKM ’11. ACM. https://doi.org/10.1145/2063576.2064044
    Project: IMPEx (2012–2015)
  • Patent image retrieval / Hanbury, A., Bhatti, N., Lupu, M., & Mörzinger, R. (2011). Patent image retrieval. In Proceedings of the 4th workshop on Patent information retrieval - PaIR ’11. ACM. https://doi.org/10.1145/2064975.2064979
    Project: IMPEx (2012–2015)

2010

  • Affective Image Classification / Machajdik, J., & Hanbury, A. (2010). Affective Image Classification. Computer Vision Winter Workshop 2010, Nove Hrady, EU. http://hdl.handle.net/20.500.12708/85619
  • Universal Seed Skin Segmentation / Khan, R., Hanbury, A., & Stöttinger, J. (2010). Universal Seed Skin Segmentation. In G. Bebis, R. Boyle, B. Parvin, D. Koracin, R. Chung, R. Hammound, M. Hussain, T. Kar-Han, R. Crawfis, D. Thalmann, D. Kao, & L. Avila (Eds.), Advances in Visual Computing (pp. 75–84). Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-642-17274-8_8
  • Augmentation of Skin Segmentation / Khan, R., Hanbury, A., & Stöttinger, J. (2010). Augmentation of Skin Segmentation. In H. Arabnia, L. Deligiannidis, G. Schaefer, & A. Solo (Eds.), Proceedings of the 2010 International Conference on Image Processing, Computer Vision, & Pattern Recognition, IPCV 2010, July 12-15, 2010, Las Vegas, Nevada, USA, 2 Volumes (pp. 473–479). CSREA Press. http://hdl.handle.net/20.500.12708/53501
  • Skin detection: A random forest approach / Khan, R., Hanbury, A., & Stoettinger, J. (2010). Skin detection: A random forest approach. In 2010 IEEE International Conference on Image Processing. International Conference on Image Processing 2010, Hong Kong, Non-EU. IEEE. https://doi.org/10.1109/icip.2010.5651638
  • Weighted Skin Color Segmentation and Detection Using Graph Cuts / Khan, R., Hanbury, A., & Stöttinger, J. (2010). Weighted Skin Color Segmentation and Detection Using Graph Cuts. In L. Spaček & V. Franc (Eds.), Proceedings of the Computer Vision Winter Workshop 2010 (pp. 107–114). Czech Society for Cybernetics and Informatics. http://hdl.handle.net/20.500.12708/53489
  • Co-occurrence Bag of Words for Object Recognition / Bhatti, N., & Hanbury, A. (2010). Co-occurrence Bag of Words for Object Recognition. In L. Spaček & V. Franc (Eds.), Proceedings of the Computer Vision Winter Workshop 2010 (pp. 21–28). Czech Society for Cybernetics and Informatics. http://hdl.handle.net/20.500.12708/53488
  • Behavior and properties of spatio-temporal local features under visual transformations / Stöttinger, J., Goras, B. T., Sebe, N., & Hanbury, A. (2010). Behavior and properties of spatio-temporal local features under visual transformations. In Proceedings of the international conference on Multimedia - MM ’10. ACM Multimedia 2010 International Conference, Florenz, Italien, EU. Association for Computing Machinery (ACM). https://doi.org/10.1145/1873951.1874174
  • FeEval A Dataset for Evaluation of Spatio-temporal Local Features / Stöttinger, J., Zambanini, S., Khan, R., & Hanbury, A. (2010). FeEval A Dataset for Evaluation of Spatio-temporal Local Features. In M. Cetin, K. Boyer, & S.-W. Lee (Eds.), 2010 20th International Conference on Pattern Recognition. IEEE. https://doi.org/10.1109/icpr.2010.128
  • Efficient and Distinct Large Scale Bags of Words / Pönitz, T., Stöttinger, J., Donner, R., & Hanbury, A. (2010). Efficient and Distinct Large Scale Bags of Words. In P. Blauensteiner, M. Lettner, & J. Stöttinger (Eds.), Computer Vision in a Global Society - 34th Annual Workshop of the Austrian Association for Pattern Recognition (AAPR) and the WG Visual Computing of the Austrian Computer Society (pp. 139–146). Österreichische Computer Gesellschaft. http://hdl.handle.net/20.500.12708/53480
  • Affective image classification using features inspired by psychology and art theory / Machajdik, J., & Hanbury, A. (2010). Affective image classification using features inspired by psychology and art theory. In Proceedings of the international conference on Multimedia - MM ’10. ACM Multimedia 2010 International Conference, Florenz, Italien, EU. Association for Computing Machinery (ACM). https://doi.org/10.1145/1873951.1873965

2009

  • Lonely but Attractive: Sparse Color Salient Points for Object Retrieval and Categorization / Stöttinger, J., Hanbury, A., Gevers, T., & Sebe, N. (2009). Lonely but Attractive: Sparse Color Salient Points for Object Retrieval and Categorization. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), Workshop on Feature Detectors and Descriptors: The State Of The Art and Beyond (pp. 1–8). http://hdl.handle.net/20.500.12708/52943
  • Morphological segmentation on learned boundaries / Hanbury, A., & Marcotegui, B. (2009). Morphological segmentation on learned boundaries. Image and Vision Computing, 27(4), 480–488. http://hdl.handle.net/20.500.12708/166247
  • Skin Paths for Contextual Flagging Adult Videos / Stöttinger, J., Hanbury, A., Liensberger, C., & Khan, R. (2009). Skin Paths for Contextual Flagging Adult Videos. In Advances in Visual Computing (pp. 303–314). Springer. http://hdl.handle.net/20.500.12708/52945
  • Translating Journalists' Requirements into Features for Image Search / Stöttinger, J., Banova, J., Ponitz, T., Sebe, N., & Hanbury, A. (2009). Translating Journalists’ Requirements into Features for Image Search. In 2009 15th International Conference on Virtual Systems and Multimedia. 15th International Conference on Virtual Systems and Multimedia ({VSMM} 2009), Wien, Austria. IEEE. https://doi.org/10.1109/vsmm.2009.28

2008

  • A survey of methods for image annotation / Hanbury, A. (2008). A survey of methods for image annotation. Journal of Visual Languages and Computing, 19, 617–627. http://hdl.handle.net/20.500.12708/170818
  • Constructing cylindrical coordinate colour spaces / Hanbury, A. (2008). Constructing cylindrical coordinate colour spaces. Pattern Recognition Letters, 29, 494–500. http://hdl.handle.net/20.500.12708/170817
  • On Segmentation Evaluation Metrics and Region Counts / Hanbury, A., & Stöttinger, J. (2008). On Segmentation Evaluation Metrics and Region Counts. In Proceedings of the the 19th International Conference on Image Processing (ICPR09). The 19th International Conference on Image Processing (ICPR08), Tampa, Florida, Non-EU. IEEE Computer Society. http://hdl.handle.net/20.500.12708/52629
  • Evaluation of Gradient Vector Flow for Interest Point Detection / Stöttinger, J., Donner, R., Szumilas, L., & Hanbury, A. (2008). Evaluation of Gradient Vector Flow for Interest Point Detection. In Advances in Visual Computing, Part I (pp. 338–348). Springer, LNCS. http://hdl.handle.net/20.500.12708/52626
  • How Do Superpixels Affect Image Segmentation? / Hanbury, A. (2008). How Do Superpixels Affect Image Segmentation? In Progress in Pattern Recognition, Image Anlysis and Applications (pp. 178–186). Springer. http://hdl.handle.net/20.500.12708/52472
  • Overview of the ImageCLEFphoto 2007 Photographic Retrieval Task / Grubinger, M., Clough, P., Hanbury, A., & Müller, H. (2008). Overview of the ImageCLEFphoto 2007 Photographic Retrieval Task. In Advances in Multilingual and Multimodal Information Retrieval (pp. 433–444). Springer. http://hdl.handle.net/20.500.12708/52471
  • Overview of the ImageCLEF 2007 Object Retrieval Task / Deselaers, T., Hanbury, A., Viitaniemi, V., Benczur, A., Brendel, M., Daroczy, B., Escalante Balderas, H. J., Gevers, T., Hernandez Gracidas, C. A., Laaksonen, J., Li, M., Marın Castro, H. M., Ney, H., Rui, X., Sebe, N., & Stöttinger, J. (2008). Overview of the ImageCLEF 2007 Object Retrieval Task. In Advances in Multilingual and Multimodal Information Retrieval (pp. 445–471). Springer. http://hdl.handle.net/20.500.12708/52470

2007

  • Improved motion segmentation based on shadow detection / Kampel, M., Wildenauer, H., Blauensteiner, P., & Hanbury, A. (2007). Improved motion segmentation based on shadow detection. Electronic Letters on Computer Vision and Image Analysis, 6(3), 12. http://hdl.handle.net/20.500.12708/169685
  • Radial Edge Configuration for Semi-local Image Structure Description / Szumilas, L., Wildenauer, H., Hanbury, A., & Donner, R. (2007). Radial Edge Configuration for Semi-local Image Structure Description. In Advances in Visual Computing (pp. 633–643). Springer Lecture Notes in Computer Science. http://hdl.handle.net/20.500.12708/52045
  • Local Structure Detection with Orientation-invariant Radial Configuration / Szumilas, L., Donner, R., Langs, G., & Hanbury, A. (2007). Local Structure Detection with Orientation-invariant Radial Configuration. In Computer Vision and Pattern Recognition (p. 7). http://hdl.handle.net/20.500.12708/52043
  • A Study of Vocabularies for Image Annotation / Hanbury, A. (2007). A Study of Vocabularies for Image Annotation. In Proceedings of the second international conference on Semantics And digital Media Technologies (SAMT) (pp. 284–287). Springer Lecture Notes in Computer Science. http://hdl.handle.net/20.500.12708/51985
  • Morphological Distinguished Regions / Hanbury, A. (2007). Morphological Distinguished Regions. In Proc. 12th Iberoamerican Congress on Pattern Recognition (CIARP). 12th Iboamerican Congress on Pattern Recognition, CIAPR2007, Vina del Mar-Valparaiso, Chile, Non-EU. Springer Lecture Notes in Computer Science. http://hdl.handle.net/20.500.12708/51983
  • Colour Adjacency Histograms for Image Matching / Hanbury, A., & Marcotegui, B. (2007). Colour Adjacency Histograms for Image Matching. In Proceedings of the Computer Analysis of Images and Patterns Conference (CAIP). 12th International Conference CAIP 2007, Wien, Austria. Springer Lecture Notes in Computer Science. http://hdl.handle.net/20.500.12708/51982
  • Do Colour Interest Points Improve Image Retrieval? / Stöttinger, J., Hanbury, A., Sebe, N., & Gevers, T. (2007). Do Colour Interest Points Improve Image Retrieval? In Proc. International Conference on Image Processing (ICIP) (pp. 169–172). http://hdl.handle.net/20.500.12708/51981
  • Image based recognition of ancient coins / Zaharieva, M., Kampel, M., & Zambanini, S. (2007). Image based recognition of ancient coins. In W. Kropatsch, M. Kampel, & A. Hanbury (Eds.), Computer Analysis of Images and Patterns (pp. 547–554). Springer Lecture Notes in Computer Science. http://hdl.handle.net/20.500.12708/51975
  • Colour Interest Points for Image Retrieval / Stöttinger, J., Sebe, N., Gevers, T., & Hanbury, A. (2007). Colour Interest Points for Image Retrieval. In Proceedings of the 12th Computer Vision Winter Workshop (pp. 83–90). http://hdl.handle.net/20.500.12708/51841
  • Computer Analysis of Images and Patterns, 12th International Conference, CAIP 2007 / Kropatsch, W., Kampel, M., & Hanbury, A. (Eds.). (2007). Computer Analysis of Images and Patterns, 12th International Conference, CAIP 2007. Springer LNCS. http://hdl.handle.net/20.500.12708/22351

2006

  • A Dataset of Annotated Animals / Hanbury, A. (2006). A Dataset of Annotated Animals. Second MUSCLE/ImageCLEF Workshop on Image and Video Retrieval Evaluation, Alicante, Spain, EU. http://hdl.handle.net/20.500.12708/84673
  • Results of the MUSCLE CIS Coin Competition 2006 / Hanbury, A. (2006). Results of the MUSCLE CIS Coin Competition 2006. MUSCLE CIS Coin Competition Workshop, Berlin, EU. http://hdl.handle.net/20.500.12708/84672
  • Analysis of Keywords used in Image Understanding Tasks / Hanbury, A. (2006). Analysis of Keywords used in Image Understanding Tasks. OntoImage International Workshop, Genova, Italy, EU. http://hdl.handle.net/20.500.12708/84671
  • The MUSCLE / ImageCLEF Image Retrieval Evaluation Campaigns / Hanbury, A. (2006). The MUSCLE / ImageCLEF Image Retrieval Evaluation Campaigns. PASCAL Visual Object Classes Challenge Workshop, Graz, Austria. http://hdl.handle.net/20.500.12708/84670
  • Overview of the ImageCLEF 2006 Photographic Retrieval and Object Annotation Tasks / Clough, P., Grubinger, M., Deselaers, T., Hanbury, A., & Müller, H. (2006). Overview of the ImageCLEF 2006 Photographic Retrieval and Object Annotation Tasks. In Proceedings of the CLEF 2006 Workshop (pp. 579–594). Springer Lecture Notes in Computer Science. http://hdl.handle.net/20.500.12708/51984
  • Motion and Shadow Detection with an Improved Colour Model / Blauensteiner, P., Wildenauer, H., Hanbury, A., & Kampel, M. (2006). Motion and Shadow Detection with an Improved Colour Model. In First International Conference on Signal and Image Processing (pp. 627–632). IEEE. http://hdl.handle.net/20.500.12708/51653
  • Motion Detection Using an Improved Colour model / Wildenauer, H., Blauensteiner, P., Hanbury, A., & Kampel, M. (2006). Motion Detection Using an Improved Colour model. In Advances in Visual Computing (pp. 607–616). Springer Berlin-Heidelberg. http://hdl.handle.net/20.500.12708/51626
  • Color Pair Clustering for Texture Detection / Szumilas, L., & Hanbury, A. (2006). Color Pair Clustering for Texture Detection. In Advances in Visual Computing (pp. 255–264). Springer. http://hdl.handle.net/20.500.12708/51583
  • Waterfall Segmentation of Complex Scenes / Hanbury, A., & Marcotegui, B. (2006). Waterfall Segmentation of Complex Scenes. In Computer Vision - ACCV 2006 (pp. 888–897). Springer. http://hdl.handle.net/20.500.12708/51544
  • On Colour Spaces for Change Detection and Shadow Suppression / Blauensteiner, P., Wildenauer, H., & Hanbury, A. (2006). On Colour Spaces for Change Detection and Shadow Suppression. In Proceedings of the 11th Computer Vision Winter Workshop (pp. 117–122). http://hdl.handle.net/20.500.12708/51543
  • Texture segmentation through salient texture patches / Szumilas, L., Micusik, B., & Hanbury, A. (2006). Texture segmentation through salient texture patches. In Proceedings of the 11th Computer Vision Winter Workshop (pp. 111–116). http://hdl.handle.net/20.500.12708/51542
  • Extraction of Attributes, Nature and Context of Images / Kuthan, S., & Hanbury, A. (2006). Extraction of Attributes, Nature and Context of Images. In Proceedings of the 11th Computer Vision Winter Workshop (pp. 28–33). http://hdl.handle.net/20.500.12708/51541
  • Fast pedestrian tracking based on spatial features and colour / Seitner, F., & Hanbury, A. (2006). Fast pedestrian tracking based on spatial features and colour. In Proceedings of the 11th Computer Vision Winter Workshop (pp. 105–110). http://hdl.handle.net/20.500.12708/51540
  • Automatic Image Segmentation by Positioning a Seed / Micusik, B., & Hanbury, A. (2006). Automatic Image Segmentation by Positioning a Seed. In Computer Vision - ECCV2006 (pp. 468–480). Springer. http://hdl.handle.net/20.500.12708/51511
  • Template patch driven image segmentation / Micusik, B., & Hanbury, A. (2006). Template patch driven image segmentation. In British Machine Vision Conference 2006, Volume Two (pp. 819–829). http://hdl.handle.net/20.500.12708/51510

2005

  • Texture Based Drawing Tool Classification in Infrared Reflectograms / Lettner, M., & Sablatnig, R. (2005). Texture Based Drawing Tool Classification in Infrared Reflectograms. In A. Hanbury & H. Bischof (Eds.), Proc. of the 10th Computer Vision Winter Workshop (pp. 63–72). Eigenverlag. http://hdl.handle.net/20.500.12708/51288
  • CCA-based Active Appearance Model Search / Donner, R., Langs, G., Reiter, M., & Bischof, H. (2005). CCA-based Active Appearance Model Search. In A. Hanbury & H. Bischof (Eds.), Computer Vision Winter Workshop 2005 (pp. 73–82). Eigenverlag. http://hdl.handle.net/20.500.12708/51329
  • Hierarchical Image Partitioning using Combinatorial Maps / Ion, A., Haxhimusa, Y., Kropatsch, W., & Brun, L. (2005). Hierarchical Image Partitioning using Combinatorial Maps. In A. Hanbury & H. Bischof (Eds.), 10th Computer Vision Winter Workshop - CVWW 2005 (pp. 43–52). Eigenverlag. http://hdl.handle.net/20.500.12708/51281
  • A Sparse Image Representation Using Contourlets / Belbachir, A. N., & Göbel, P. (2005). A Sparse Image Representation Using Contourlets. In A. Hanbury & H. Bischof (Eds.), Proc. of 10th Computer Vision Winter Workshop (pp. 165–174). Eigenverlag. http://hdl.handle.net/20.500.12708/51318
  • Semi-automatic Segmentation of Textured Images / Micusik, B., & Hanbury, A. (2005). Semi-automatic Segmentation of Textured Images. In A. Hanbury & H. Bischof (Eds.), Proceedings of the 10th Computer Vision Winter Workshop (CVWW 2005) (pp. 53–62). Eigenverlag. http://hdl.handle.net/20.500.12708/51315
  • Classification of Color Pigments in Hyperspectral Images / Asinger, C., Kammerer, P., & Zolda, E. (2005). Classification of Color Pigments in Hyperspectral Images. In A. Hanbury & H. Bischof (Eds.), Proc. of the 10th Computer Vision Winter Workshop (pp. 205–214). Eigenverlag. http://hdl.handle.net/20.500.12708/51332
  • MDL-based Splitting of PCA Models / Langs, G., Peloschek, P. L., & Bischof, H. (2005). MDL-based Splitting of PCA Models. In A. Hanbury & H. Bischof (Eds.), Proceedings of Computer Vision Winter Workshop CVWW (pp. 13–22). Eigenverlag. http://hdl.handle.net/20.500.12708/51296
  • Segmentation and Surveying of Cutaneous Hemangiomas / Zambanini, S., Langs, G., & Bischof, H. (2005). Segmentation and Surveying of Cutaneous Hemangiomas. In A. Hanbury & H. Bischof (Eds.), Proceedings of Computer Vision Winter Workshop CVWW (pp. 103–112). Eigenverlag. http://hdl.handle.net/20.500.12708/51297
  • Robust Detection and Performance Evaluation of Individuals and Vehicles on an Airport's Apron / Aguilera Antequera, J., Kampel, M., & Blauensteiner, P. (2005). Robust Detection and Performance Evaluation of Individuals and Vehicles on an Airport’s Apron. In A. Hanbury & H. Bischof (Eds.), In Proc. of the Computer Vision Winter Workshop (pp. 145–154). Eigenverlag. http://hdl.handle.net/20.500.12708/51298
  • Proceedings of the 10th Computer Vision Winter Workshop CVWW 2005 / Hanbury, A., & Bischof, H. (Eds.). (2005). Proceedings of the 10th Computer Vision Winter Workshop CVWW 2005. Eigenverlag. http://hdl.handle.net/20.500.12708/22302
  • A Method for Determining Geometrical Distortion of Off-The-Shelf Wide-Angle Cameras / Zollner, H., & Sablatnig, R. (2005). A Method for Determining Geometrical Distortion of Off-The-Shelf Wide-Angle Cameras. In W. Kropatsch, R. Sablatnig, & A. Hanbury (Eds.), Proc. of the 27th DAGM Symposium (pp. 224–229). Springer, LNCS. http://hdl.handle.net/20.500.12708/51328
  • Blind Background Substraction in Dental Panoramic X-ray Images: An Application Approach / Göbel, P., & Belbachir, A. N. (2005). Blind Background Substraction in Dental Panoramic X-ray Images: An Application Approach. In W. Kropatsch, R. Sablatnig, & A. Hanbury (Eds.), Proc. of the 27th DAGM Symposium (pp. 434–441). Springer, LNCS. http://hdl.handle.net/20.500.12708/51320
  • Color Image Compression: Early Vision and the Multiresolution Representations / Belbachir, A. N., & Göbel, P. (2005). Color Image Compression: Early Vision and the Multiresolution Representations. In W. Kropatsch, R. Sablatnig, & A. Hanbury (Eds.), Proc. of the 27th DAGM Symposium (pp. 25–32). Springer, LNCS. http://hdl.handle.net/20.500.12708/51319
  • Steerable Semi-automatic Segmentation of Textured Images / Micusik, B., & Hanbury, A. (2005). Steerable Semi-automatic Segmentation of Textured Images. In H. Kalviainen, J. Parkkinen, & A. Kaarna (Eds.), 14th Scandinavian Conference on Image Analysis (SCIA) (pp. 35–44). Springer, LNCS. http://hdl.handle.net/20.500.12708/51316
  • Supervised Texture Detection in Images / Micusik, B., & Hanbury, A. (2005). Supervised Texture Detection in Images. In A. Gagalowicz & W. Philips (Eds.), Computer Analysis of Images and Patterns (CAI (pp. 441–448). Springer, LNCS. http://hdl.handle.net/20.500.12708/51314
  • Illumination-invariant morphological texture classification / Hanbury, A., Kandaswamy, U., & Adjeroh, D. (2005). Illumination-invariant morphological texture classification. In C. Ronse, L. Najman, & E. Decenciere (Eds.), Proceedings of the International Symposium on Mathematical Morphology (pp. 377–386). Springer. http://hdl.handle.net/20.500.12708/51313
  • Pattern Recognition: 27th DAGM Symposium / Kropatsch, W., Sablatnig, R., & Hanbury, A. (Eds.). (2005). Pattern Recognition: 27th DAGM Symposium. Springer, LNCS. http://hdl.handle.net/20.500.12708/22301

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2009

  • Affective image classification / Machajdik, J. (2009). Affective image classification [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://resolver.obvsg.at/urn:nbn:at:at-ubtuw:1-35156
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2005