Babak Ehteshami Bejnordi

According to our database, Babak Ehteshami Bejnordi authored at least 32 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2024

Read-ME: Refactorizing LLMs as Router-Decoupled Mixture of Experts with System Co-Design.

Ruisi Cai, Yeonju Ro, Geon-Woo Kim, Peihao Wang, Babak Ehteshami Bejnordi, Aditya Akella, Zhangyang Wang

CoRR, 2024

InterroGate: Learning to Share, Specialize, and Prune Representations for Multi-task Learning.

Babak Ehteshami Bejnordi, Gaurav Kumar, Amelie Royer, Christos Louizos, Tijmen Blankevoort, Mohsen Ghafoorian

CoRR, 2024

Think Big, Generate Quick: LLM-to-SLM for Fast Autoregressive Decoding.

Benjamin Bergner, Andrii Skliar, Amelie Royer, Tijmen Blankevoort, Yuki M. Asano, Babak Ehteshami Bejnordi

CoRR, 2024

2023

Computational Pathology: A Survey Review and The Way Forward.

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

CoRR, 2023

Scalarization for Multi-Task and Multi-Domain Learning at Scale.

Amelie Royer, Tijmen Blankevoort, Babak Ehteshami Bejnordi

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

RCV2023 Challenges: Benchmarking Model Training and Inference for Resource-Constrained Deep Learning.

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

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

MSViT: Dynamic Mixed-scale Tokenization for Vision Transformers.

Jakob Drachmann Havtorn, Amélie Royer, Tijmen Blankevoort, Babak Ehteshami Bejnordi

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022

SALISA: Saliency-Based Input Sampling for Efficient Video Object Detection.

Babak Ehteshami Bejnordi, Amirhossein Habibian, Fatih Porikli, Amir Ghodrati

Proceedings of the Computer Vision - ECCV 2022, 2022

Revisiting single-gated Mixtures of Experts.

Amelie Royer, Ilia Karmanov, Andrii Skliar, Babak Ehteshami Bejnordi, Tijmen Blankevoort

Proceedings of the 33rd British Machine Vision Conference 2022, 2022

2021

Skip-Convolutions for Efficient Video Processing.

Amirhossein Habibian, Davide Abati, Taco S. Cohen, Babak Ehteshami Bejnordi

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

FrameExit: Conditional Early Exiting for Efficient Video Recognition.

Amir Ghodrati, Babak Ehteshami Bejnordi, Amirhossein Habibian

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

TimeGate: Conditional Gating of Segments in Long-range Activities.

Noureldien Hussein, Mihir Jain, Babak Ehteshami Bejnordi

CoRR, 2020

Batch-shaping for learning conditional channel gated networks.

Babak Ehteshami Bejnordi, Tijmen Blankevoort, Max Welling

Proceedings of the 8th International Conference on Learning Representations, 2020

Conditional Channel Gated Networks for Task-Aware Continual Learning.

Davide Abati, Jakub Tomczak, Tijmen Blankevoort, Simone Calderara, Rita Cucchiara, Babak Ehteshami Bejnordi

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

From Detection of Individual Metastases to Classification of Lymph Node Status at the Patient Level: The CAMELYON17 Challenge.

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

IEEE Trans. Medical Imaging, 2019

Predicting breast tumor proliferation from whole-slide images: The TUPAC16 challenge.

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

Medical Image Anal., 2019

Batch-Shaped Channel Gated Networks.

Babak Ehteshami Bejnordi, Tijmen Blankevoort, Max Welling

CoRR, 2019

2018

Predicting breast tumor proliferation from whole-slide images: the TUPAC16 challenge.

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

CoRR, 2018

Stain normalization of histopathology images using generative adversarial networks.

Farhad Ghazvinian Zanjani, Svitlana Zinger, Babak Ehteshami Bejnordi, Jeroen A. W. M. van der Laak, Peter H. N. de With

Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

2017

A survey on deep learning in medical image analysis.

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

Medical Image Anal., 2017

Context-aware stacked convolutional neural networks for classification of breast carcinomas in whole-slide histopathology images.

Babak Ehteshami Bejnordi, Guido C. A. Zuidhof, Maschenka Balkenhol, Meyke Hermsen, Peter Bult, Bram van Ginneken, Nico Karssemeijer, Geert Litjens, Jeroen van der Laak

CoRR, 2017

The importance of stain normalization in colorectal tissue classification with convolutional networks.

Francesco Ciompi, Oscar Geessink, Babak Ehteshami Bejnordi, Gabriel Silva de Souza, Alexi Baidoshvili, Geert Litjens, Bram van Ginneken, Iris Nagtegaal, Jeroen van der Laak

Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017

Deep learning-based assessment of tumor-associated stroma for diagnosing breast cancer in histopathology images.

Babak Ehteshami Bejnordi, Jimmy Lin, Ben Glass, Maeve Mullooly, Gretchen L. Gierach, Mark E. Sherman, Nico Karssemeijer, Jeroen van der Laak, Andrew H. Beck

Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017

2016

Stain Specific Standardization of Whole-Slide Histopathological Images.

Babak Ehteshami Bejnordi, Geert Litjens, Nadya Timofeeva, Irene Otte-Höller, André Homeyer, Nico Karssemeijer, Jeroen A. W. M. van der Laak

IEEE Trans. Medical Imaging, 2016

Automated Detection of DCIS in Whole-Slide H&E Stained Breast Histopathology Images.

Babak Ehteshami Bejnordi, Maschenka Balkenhol, Geert Litjens, Roland Holland, Peter Bult, Nico Karssemeijer, Jeroen A. W. M. van der Laak

IEEE Trans. Medical Imaging, 2016

Whole Mastectomy Volume Reconstruction from 2D Radiographs and Its Mapping to Histology.

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

Proceedings of the Breast Imaging, 2016

2015

Automated detection of prostate cancer in digitized whole-slide images of H and E-stained biopsy specimens.

Geert Litjens, Babak Ehteshami Bejnordi, Nadya Timofeeva, G. Swadi, Iringo Kovacs, Christina A. Hulsbergen van de Kaa, Jeroen van der Laak

Proceedings of the Medical Imaging 2015: Digital Pathology, 2015

A multi-scale superpixel classification approach to the detection of regions of interest in whole slide histopathology images.

Babak Ehteshami Bejnordi, Geert Litjens, Meyke Hermsen, Nico Karssemeijer, Jeroen A. W. M. van der Laak

Proceedings of the Medical Imaging 2015: Digital Pathology, 2015

A novel spherical shell filter for reducing false positives in automatic detection of pulmonary nodules in thoracic CT scans.

Sil C. van de Leemput, Frank Dorssers, Babak Ehteshami Bejnordi

Proceedings of the Medical Imaging 2015: Computer-Aided Diagnosis, 2015

2014

Quantitative analysis of stain variability in histology slides and an algorithm for standardization.

Babak Ehteshami Bejnordi, Nadya Timofeeva, Irene Otte-Höller, Nico Karssemeijer, Jeroen A. W. M. van der Laak

Proceedings of the Medical Imaging 2014: Digital Pathology, 2014

2013

Novel chromatin texture features for the classification of pap smears.

Babak Ehteshami Bejnordi, Ramin Moshavegh, K. Sujathan, Patrik Malm, Ewert Bengtsson, Andrew Mehnert

Proceedings of the Medical Imaging 2013: Digital Pathology, 2013

2012

Automated segmentation of free-lying cell nuclei in Pap smears for malignancy-associated change analysis.

Ramin Moshavegh, Babak Ehteshami Bejnordi, Andrew Mehnert, K. Sujathan, Patrik Malm, Ewert Bengtsson

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012