TU Wien Informatics

20 Years
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Zahra Babaiee

Projektass.in(FWF)

Zahra Babaiee

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  • Unveiling the Unseen: Identifiable Clusters in Trained Depthwise Convolutional Kernels / Babaiee, Z., Mohseni Kiasari, P., Rus, D., & Grosu, R. (2024). Unveiling the Unseen: Identifiable Clusters in Trained Depthwise Convolutional Kernels. In The Twelth International Conference on Learning Representations, ICLR 2024, Vienna, Austria, May 7-11, 2024. The Twelfth International Conference on Learning Representations (ICLR 2024), Austria. http://hdl.handle.net/20.500.12708/203933
  • Neural Echos: Depthwise Convolutional Filters Replicate Biological Receptive Fields / Babaiee, Z., Mohseni Kiasari, P., Rus, D., & Grosu, R. (2024). Neural Echos: Depthwise Convolutional Filters Replicate Biological Receptive Fields. In 2024 IEEE Winter Conference on Applications of Computer Vision (pp. 8216–8225). https://doi.org/10.1109/WACV57701.2024.00803
    Project: MATTO-GBM (2024–2027)
  • Investigation and benchmarking of U-Nets on prostate segmentation tasks / Bhandary, S., Kuhn, D., Babaiee, Z., Fechter, T., Benndorf, M., Zamboglou, C., Grosu, A.-L., & Grosu, R. (2023). Investigation and benchmarking of U-Nets on prostate segmentation tasks. Computerized Medical Imaging and Graphics, 107, Article 102241. https://doi.org/10.1016/j.compmedimag.2023.102241
    Download: PDF (1.58 MB)
    Project: PersoRad (2020–2023)
  • Deep-Learning vs Regression: Prediction of Tourism Flow with Limited Data / Lemmel, J., Babaiee, Z., Kleinlehner, M., Majic, I., Neubauer, P., Scholz, J., Grosu, R., & Neubauer, S. (2022). Deep-Learning vs Regression: Prediction of Tourism Flow with Limited Data. In Schedule - IJCAI’22 Workshop. AI4TS: AI for Time Series Analysis. IJCAI’22 Workshop - AI4TS: AI for Time Series Analysis, Vienna, Austria. IJCAI. https://doi.org/10.34726/4262
    Download: PDF (257 KB)
  • On-Off Center-Surround Receptive Fields for Accurate and Robust Image Classification / Babaiee, Z., Hasani, R., Lechner, M., Rus, D., & Grosu, R. (2021). On-Off Center-Surround Receptive Fields for Accurate and Robust Image Classification. In International Conference on Machine Learning (pp. 478–489). Proceedings of Machine Learning Research. http://hdl.handle.net/20.500.12708/55625