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ORCIDBabak Ehteshami Bejnordi
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2020 – today
- 2024
[i17]Benjamin Bergner, Andrii Skliar, Amelie Royer, Tijmen Blankevoort, Yuki M. Asano, Babak Ehteshami Bejnordi:
Think Big, Generate Quick: LLM-to-SLM for Fast Autoregressive Decoding. CoRR abs/2402.16844 (2024)- [i16]Babak Ehteshami Bejnordi, Gaurav Kumar, Amelie Royer, Christos Louizos, Tijmen Blankevoort, Mohsen Ghafoorian:
InterroGate: Learning to Share, Specialize, and Prune Representations for Multi-task Learning. CoRR abs/2402.16848 (2024) - 2023
- [c19]Jakob Drachmann Havtorn, Amélie Royer, Tijmen Blankevoort, Babak Ehteshami Bejnordi:
MSViT: Dynamic Mixed-scale Tokenization for Vision Transformers. ICCV (Workshops) 2023: 838-848 - [c18]Rishabh Tiwari, Arnav Chavan, Deepak K. Gupta, Gowreesh Mago, Animesh Gupta, Akash Gupta, Suraj Sharan, Yukun Yang, Shanwei Zhao, Shihao Wang, Youngjun Kwak, Seonghun Jeong, Yunseung Lee, Changick Kim, Subin Kim, Ganzorig Gankhuyag, Ho Jung, Junwhan Ryu, HaeMoon Kim, Byeong Hak Kim, Tu Vo, Sheir Zaheer, Alexander Holston, Chan Y. Park, Dheemant Dixit, Nahush Lele, Kushagra Bhushan, Debjani Bhowmick, Devanshu Arya, Sadaf Gulshad, Amirhossein Habibian, Amir Ghodrati, Babak Ehteshami Bejnordi, Jai Gupta, Zhuang Liu, Jiahui Yu, Dilip K. Prasad, Zhiqiang Shen:
RCV2023 Challenges: Benchmarking Model Training and Inference for Resource-Constrained Deep Learning. ICCV (Workshops) 2023: 1526-1535 - [c17]Amelie Royer, Tijmen Blankevoort, Babak Ehteshami Bejnordi:
Scalarization for Multi-Task and Multi-Domain Learning at Scale. NeurIPS 2023 - [i15]Mahdi S. Hosseini, Babak Ehteshami Bejnordi, Vincent Quoc-Huy Trinh, Danial Hasan, Xingwen Li, Taehyo Kim, Haochen Zhang, Theodore Wu, Kajanan Chinniah, Sina Maghsoudlou, Ryan Zhang, Stephen Yang, Jiadai Zhu, Lyndon Chan, Samir Khaki, Andrei Buin, Fatemeh Chaji, Ala Salehi, Alejandra Zambrano Luna, Bich Ngoc Nguyen, Dimitris Samaras, Konstantinos N. Plataniotis:
Computational Pathology: A Survey Review and The Way Forward. CoRR abs/2304.05482 (2023) - [i14]Amelie Royer, Ilia Karmanov, Andrii Skliar, Babak Ehteshami Bejnordi, Tijmen Blankevoort:
Revisiting Single-gated Mixtures of Experts. CoRR abs/2304.05497 (2023) - [i13]Jakob Drachmann Havtorn, Amelie Royer, Tijmen Blankevoort, Babak Ehteshami Bejnordi:
MSViT: Dynamic Mixed-Scale Tokenization for Vision Transformers. CoRR abs/2307.02321 (2023) - [i12]Amelie Royer, Tijmen Blankevoort, Babak Ehteshami Bejnordi:
Scalarization for Multi-Task and Multi-Domain Learning at Scale. CoRR abs/2310.08910 (2023) - 2022
- [c16]Amelie Royer, Ilia Karmanov, Andrii Skliar, Babak Ehteshami Bejnordi, Tijmen Blankevoort:
Revisiting single-gated Mixtures of Experts. BMVC 2022: 736 - [c15]Babak Ehteshami Bejnordi, Amirhossein Habibian, Fatih Porikli, Amir Ghodrati:
SALISA: Saliency-Based Input Sampling for Efficient Video Object Detection. ECCV (10) 2022: 300-316 - [i11]Babak Ehteshami Bejnordi, Amirhossein Habibian, Fatih Porikli, Amir Ghodrati:
SALISA: Saliency-based Input Sampling for Efficient Video Object Detection. CoRR abs/2204.02397 (2022) - 2021
- [c14]Amirhossein Habibian, Davide Abati, Taco S. Cohen, Babak Ehteshami Bejnordi:
Skip-Convolutions for Efficient Video Processing. CVPR 2021: 2695-2704 - [c13]Amir Ghodrati, Babak Ehteshami Bejnordi, Amirhossein Habibian:
FrameExit: Conditional Early Exiting for Efficient Video Recognition. CVPR 2021: 15608-15618 - [i10]Amirhossein Habibian, Davide Abati, Taco S. Cohen, Babak Ehteshami Bejnordi:
Skip-Convolutions for Efficient Video Processing. CoRR abs/2104.11487 (2021) - [i9]Amir Ghodrati, Babak Ehteshami Bejnordi, Amirhossein Habibian:
FrameExit: Conditional Early Exiting for Efficient Video Recognition. CoRR abs/2104.13400 (2021) - 2020
- [c12]Davide Abati, Jakub Tomczak, Tijmen Blankevoort, Simone Calderara, Rita Cucchiara, Babak Ehteshami Bejnordi:
Conditional Channel Gated Networks for Task-Aware Continual Learning. CVPR 2020: 3930-3939 - [c11]Babak Ehteshami Bejnordi, Tijmen Blankevoort, Max Welling:
Batch-shaping for learning conditional channel gated networks. ICLR 2020 - [i8]Davide Abati, Jakub Tomczak, Tijmen Blankevoort, Simone Calderara, Rita Cucchiara, Babak Ehteshami Bejnordi:
Conditional Channel Gated Networks for Task-Aware Continual Learning. CoRR abs/2004.00070 (2020) - [i7]Noureldien Hussein
, Mihir Jain, Babak Ehteshami Bejnordi:
TimeGate: Conditional Gating of Segments in Long-range Activities. CoRR abs/2004.01808 (2020)
2010 – 2019
- 2019
- [j5]Mitko Veta, Yujing J. Heng, Nikolas Stathonikos, Babak Ehteshami Bejnordi, Francisco Beca, Thomas Wollmann, Karl Rohr, Manan A. Shah, Dayong Wang, Mikaël Rousson, Martin Hedlund, David Tellez, Francesco Ciompi, Erwan Zerhouni, David Lanyi, Matheus Palhares Viana, Vassili Kovalev, Vitali Liauchuk, Josien P. W. Pluim:
Predicting breast tumor proliferation from whole-slide images: The TUPAC16 challenge. Medical Image Anal. 54: 111-121 (2019) - [j4]Péter Bándi, Oscar Geessink, Quirine Manson, Marcory Van Dijk, Maschenka Balkenhol, Meyke Hermsen, Babak Ehteshami Bejnordi, Byungjae Lee, Kyunghyun Paeng, Aoxiao Zhong, Quanzheng Li, Farhad Ghazvinian Zanjani, Svitlana Zinger, Keisuke Fukuta, Daisuke Komura, Vlado Ovtcharov, Shenghua Cheng, Shaoqun Zeng, Jeppe Thagaard, Anders B. Dahl, Huangjing Lin, Hao Chen, Ludwig Jacobsson, Martin Hedlund, Melih Çetin, Eren Halici, Hunter Jackson, Richard Chen, Fabian Both, Jörg Franke, Heidi Küsters-Vandevelde, Willem Vreuls, Peter Bult, Bram van Ginneken, Jeroen van der Laak, Geert Litjens:
From Detection of Individual Metastases to Classification of Lymph Node Status at the Patient Level: The CAMELYON17 Challenge. IEEE Trans. Medical Imaging 38(2): 550-560 (2019) - [i6]Babak Ehteshami Bejnordi, Tijmen Blankevoort, Max Welling:
Batch-Shaped Channel Gated Networks. CoRR abs/1907.06627 (2019) - 2018
- [c10]Farhad Ghazvinian Zanjani, Svitlana Zinger, Babak Ehteshami Bejnordi, Jeroen A. W. M. van der Laak, Peter H. N. de With:
Stain normalization of histopathology images using generative adversarial networks. ISBI 2018: 573-577 - [i5]Mitko Veta, Yujing J. Heng, Nikolas Stathonikos, Babak Ehteshami Bejnordi, Francisco Beca, Thomas Wollmann, Karl Rohr, Manan A. Shah, Dayong Wang, Mikaël Rousson, Martin Hedlund, David Tellez, Francesco Ciompi, Erwan Zerhouni, David Lanyi, Matheus Palhares Viana, Vassili Kovalev, Vitali Liauchuk, Hady Ahmady Phoulady, Talha Qaiser, Simon Graham, Nasir M. Rajpoot, Erik Sjöblom, Jesper Molin, Kyunghyun Paeng, Sangheum Hwang, Sunggyun Park, Zhipeng Jia, Eric I-Chao Chang, Yan Xu, Andrew H. Beck, Paul J. van Diest, Josien P. W. Pluim:
Predicting breast tumor proliferation from whole-slide images: the TUPAC16 challenge. CoRR abs/1807.08284 (2018) - 2017
- [j3]Geert Litjens, Thijs Kooi, Babak Ehteshami Bejnordi, Arnaud Arindra Adiyoso Setio, Francesco Ciompi, Mohsen Ghafoorian, Jeroen A. W. M. van der Laak, Bram van Ginneken, Clara I. Sánchez:
A survey on deep learning in medical image analysis. Medical Image Anal. 42: 60-88 (2017) - [c9]Francesco Ciompi, Oscar Geessink, Babak Ehteshami Bejnordi, Gabriel Silva de Souza, Alexi Baidoshvili, Geert Litjens, Bram van Ginneken, Iris Nagtegaal, Jeroen van der Laak:
The importance of stain normalization in colorectal tissue classification with convolutional networks. ISBI 2017: 160-163 - [c8]Babak Ehteshami Bejnordi, Jimmy Lin, Ben Glass, Maeve Mullooly, Gretchen L. Gierach, Mark E. Sherman, Nico Karssemeijer, Jeroen van der Laak, Andrew H. Beck:
Deep learning-based assessment of tumor-associated stroma for diagnosing breast cancer in histopathology images. ISBI 2017: 929-932 - [i4]Geert Litjens, Thijs Kooi, Babak Ehteshami Bejnordi, Arnaud Arindra Adiyoso Setio, Francesco Ciompi, Mohsen Ghafoorian, Jeroen A. W. M. van der Laak, Bram van Ginneken, Clara I. Sánchez:
A Survey on Deep Learning in Medical Image Analysis. CoRR abs/1702.05747 (2017) - [i3]Babak Ehteshami Bejnordi, Jimmy Lin, Ben Glass, Maeve Mullooly, Gretchen L. Gierach, Mark E. Sherman, Nico Karssemeijer, Jeroen van der Laak, Andrew H. Beck:
Deep learning-based assessment of tumor-associated stroma for diagnosing breast cancer in histopathology images. CoRR abs/1702.05803 (2017) - [i2]Francesco Ciompi, Oscar Geessink, Babak Ehteshami Bejnordi, Gabriel Silva de Souza, Alexi Baidoshvili, Geert Litjens, Bram van Ginneken, Iris Nagtegaal, Jeroen van der Laak:
The importance of stain normalization in colorectal tissue classification with convolutional networks. CoRR abs/1702.05931 (2017) - [i1]Babak Ehteshami Bejnordi, Guido C. A. Zuidhof, Maschenka Balkenhol, Meyke Hermsen, Peter Bult, Bram van Ginneken, Nico Karssemeijer, Geert Litjens, Jeroen van der Laak:
Context-aware stacked convolutional neural networks for classification of breast carcinomas in whole-slide histopathology images. CoRR abs/1705.03678 (2017) - 2016
- [j2]Babak Ehteshami Bejnordi, Geert Litjens, Nadya Timofeeva, Irene Otte-Höller, André Homeyer, Nico Karssemeijer, Jeroen A. W. M. van der Laak:
Stain Specific Standardization of Whole-Slide Histopathological Images. IEEE Trans. Medical Imaging 35(2): 404-415 (2016) - [j1]Babak Ehteshami Bejnordi, Maschenka Balkenhol, Geert Litjens, Roland Holland, Peter Bult, Nico Karssemeijer, Jeroen A. W. M. van der Laak:
Automated Detection of DCIS in Whole-Slide H&E Stained Breast Histopathology Images. IEEE Trans. Medical Imaging 35(9): 2141-2150 (2016) - [c7]Thomy Mertzanidou, John H. Hipwell, Sara Reis, Babak Ehteshami Bejnordi, Meyke Hermsen, Mehmet Dalmis, Suzan Vreemann, Bram Platel, Jeroen van der Laak, Nico Karssemeijer, Ritse Mann, Peter Bult, David J. Hawkes:
Whole Mastectomy Volume Reconstruction from 2D Radiographs and Its Mapping to Histology. Digital Mammography / IWDM 2016: 367-374 - 2015
- [c6]Sil C. van de Leemput, Frank Dorssers, Babak Ehteshami Bejnordi:
A novel spherical shell filter for reducing false positives in automatic detection of pulmonary nodules in thoracic CT scans. Medical Imaging: Computer-Aided Diagnosis 2015: 94142P - [c5]Babak Ehteshami Bejnordi, Geert Litjens, Meyke Hermsen, Nico Karssemeijer, Jeroen A. W. M. van der Laak:
A multi-scale superpixel classification approach to the detection of regions of interest in whole slide histopathology images. Medical Imaging: Digital Pathology 2015: 94200H - [c4]Geert Litjens, Babak Ehteshami Bejnordi, Nadya Timofeeva, G. Swadi, Iringo Kovacs, Christina A. Hulsbergen van de Kaa, Jeroen van der Laak:
Automated detection of prostate cancer in digitized whole-slide images of H and E-stained biopsy specimens. Medical Imaging: Digital Pathology 2015: 94200B - 2014
- [c3]Babak Ehteshami Bejnordi, Nadya Timofeeva, Irene Otte-Höller, Nico Karssemeijer, Jeroen A. W. M. van der Laak:
Quantitative analysis of stain variability in histology slides and an algorithm for standardization. Medical Imaging: Digital Pathology 2014: 904108 - 2013
- [c2]Babak Ehteshami Bejnordi, Ramin Moshavegh, K. Sujathan, Patrik Malm, Ewert Bengtsson, Andrew Mehnert:
Novel chromatin texture features for the classification of pap smears. Medical Imaging: Digital Pathology 2013: 867608 - 2012
- [c1]Ramin Moshavegh, Babak Ehteshami Bejnordi, Andrew Mehnert, K. Sujathan, Patrik Malm, Ewert Bengtsson:
Automated segmentation of free-lying cell nuclei in Pap smears for malignancy-associated change analysis. EMBC 2012: 5372-5375
Coauthor Index
aka: Jeroen A. W. M. van der Laak
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