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ORCIDKrishna Chaitanya
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2020 – today
- 2024
[c18]Pooya Mobadersany, Chaitanya Parmar, Pablo F. Damasceno, Shreyas Fadnavis, Krishna Chaitanya, Shilong Li, Evan Schwab, Jaclyn Xiao, Lindsey Surace, Tommaso Mansi, Gabriela Oana Cula, Louis Ghanem, Kristopher Standish:
Harnessing Temporal Information for Precise Frame-Level Predictions in Endoscopy Videos. MICCAI (6) 2024: 295-305- [c17]Krishna Chaitanya, Pablo F. Damasceno, Shreyas Fadnavis, Pooya Mobadersany, Chaitanya Parmar, Emily Scherer, Natalia Zemlianskaia, Lindsey Surace, Louis Ghanem, Gabriela Oana Cula, Tommaso Mansi, Kristopher Standish:
Arges: Spatio-Temporal Transformer for Ulcerative Colitis Severity Assessment in Endoscopy Videos. MLMI@MICCAI (2) 2024: 201-211 - 2023
- [j3]Krishna Chaitanya
, Ertunc Erdil, Neerav Karani, Ender Konukoglu:
Local contrastive loss with pseudo-label based self-training for semi-supervised medical image segmentation. Medical Image Anal. 87: 102792 (2023) - [c16]Islam Torky, Simon Ruth, Shashi Sharma, Mohamed Salama, Krishna Chaitanya, Tim Gollub, Johannes Kiesel, Benno Stein:
Webis @ ImageArg 2023: Embedding-based Stance and Persuasiveness Classification. ArgMining@EMNLP 2023: 157-161 - [c15]Gustav Bredell, Kyriakos Flouris, Krishna Chaitanya, Ertunc Erdil, Ender Konukoglu:
Explicitly Minimizing the Blur Error of Variational Autoencoders. ICLR 2023 - [i14]Gustav Bredell, Kyriakos Flouris, Krishna Chaitanya, Ertunc Erdil, Ender Konukoglu:
Explicitly Minimizing the Blur Error of Variational Autoencoders. CoRR abs/2304.05939 (2023) - 2022
- [b1]Krishna Chaitanya:
Accurate Medical Image Segmentation with Limited Annotations. ETH Zurich, Zürich, Switzerland, 2022 - [c14]Krishna Chaitanya, Chloé Audigier, Laura Elena Balascuta, Tommaso Mansi:
Automatic planning of liver tumor thermal ablation using deep reinforcement learning. MIDL 2022: 219-230 - [i13]Neerav Karani, Georg Brunner, Ertunc Erdil, Simin Fei, Kerem Can Tezcan, Krishna Chaitanya, Ender Konukoglu:
A Field of Experts Prior for Adapting Neural Networks at Test Time. CoRR abs/2202.05271 (2022) - 2021
- [j2]Neerav Karani, Ertunc Erdil, Krishna Chaitanya, Ender Konukoglu:
Test-time adaptable neural networks for robust medical image segmentation. Medical Image Anal. 68: 101907 (2021) - [j1]Krishna Chaitanya, Neerav Karani, Christian F. Baumgartner, Ertunc Erdil, Anton S. Becker, Olivio Donati, Ender Konukoglu:
Semi-supervised task-driven data augmentation for medical image segmentation. Medical Image Anal. 68: 101934 (2021) - [c13]Hongwei Li, Fei-Fei Xue, Krishna Chaitanya, Shengda Luo, Ivan Ezhov, Benedikt Wiestler, Jianguo Zhang, Bjoern H. Menze:
Imbalance-Aware Self-supervised Learning for 3D Radiomic Representations. MICCAI (2) 2021: 36-46 - [c12]Ertunc Erdil, Krishna Chaitanya, Neerav Karani, Ender Konukoglu:
Task-Agnostic Out-of-Distribution Detection Using Kernel Density Estimation. UNSURE/PIPPI@MICCAI 2021: 91-101 - [c11]Alexis Perakis, Ali Gorji, Samriddhi Jain, Krishna Chaitanya, Simone Rizza, Ender Konukoglu:
Contrastive Learning of Single-Cell Phenotypic Representations for Treatment Classification. MLMI@MICCAI 2021: 565-575 - [i12]Hongwei Li, Fei-Fei Xue, Krishna Chaitanya, Shengda Liu, Ivan Ezhov, Benedikt Wiestler, Jianguo Zhang, Bjoern H. Menze:
Imbalance-Aware Self-Supervised Learning for 3D Radiomic Representations. CoRR abs/2103.04167 (2021) - [i11]Alexis Perakis, Ali Gorji, Samriddhi Jain, Krishna Chaitanya, Simone Rizza, Ender Konukoglu:
Contrastive Learning of Single-Cell Phenotypic Representations for Treatment Classification. CoRR abs/2103.16670 (2021) - [i10]Krishna Chaitanya, Ertunc Erdil, Neerav Karani, Ender Konukoglu:
Local contrastive loss with pseudo-label based self-training for semi-supervised medical image segmentation. CoRR abs/2112.09645 (2021) - 2020
- [c10]Pooja Singh, Krishna Chaitanya, Sonali, Abhishek Dixit, Virander Kumar Jain:
Study of Performance Enhancement in Underwater Optical Wireless Communication System. IEEE ANTS 2020: 1-6 - [c9]Krishna Chaitanya, Ertunc Erdil, Neerav Karani, Ender Konukoglu:
Contrastive learning of global and local features for medical image segmentation with limited annotations. NeurIPS 2020 - [i9]Neerav Karani, Krishna Chaitanya, Ender Konukoglu:
Test-Time Adaptable Neural Networks for Robust Medical Image Segmentation. CoRR abs/2004.04668 (2020) - [i8]Krishna Chaitanya, Ertunc Erdil, Neerav Karani, Ender Konukoglu:
Contrastive learning of global and local features for medical image segmentation with limited annotations. CoRR abs/2006.10511 (2020) - [i7]Ertunc Erdil, Krishna Chaitanya, Ender Konukoglu:
Unsupervised out-of-distribution detection using kernel density estimation. CoRR abs/2006.10712 (2020) - [i6]Krishna Chaitanya, Neerav Karani, Christian F. Baumgartner, Anton S. Becker, Olivio Donati, Ender Konukoglu:
Semi-supervised Task-driven Data Augmentation for Medical Image Segmentation. CoRR abs/2007.05363 (2020)
2010 – 2019
- 2019
- [c8]Krishna Chaitanya, Neerav Karani, Christian F. Baumgartner, Anton S. Becker, Olivio Donati, Ender Konukoglu:
Semi-supervised and Task-Driven Data Augmentation. IPMI 2019: 29-41 - [c7]Christian F. Baumgartner, Kerem Can Tezcan, Krishna Chaitanya, Andreas M. Hötker, Urs J. Muehlematter, Khoschy Schawkat, Anton S. Becker, Olivio Donati, Ender Konukoglu:
PHiSeg: Capturing Uncertainty in Medical Image Segmentation. MICCAI (2) 2019: 119-127 - [i5]Krishna Chaitanya, Neerav Karani, Christian F. Baumgartner, Olivio Donati, Anton S. Becker, Ender Konukoglu:
Semi-Supervised and Task-Driven Data Augmentation. CoRR abs/1902.05396 (2019) - [i4]Christian F. Baumgartner, Kerem Can Tezcan, Krishna Chaitanya, Andreas M. Hötker, Urs J. Muehlematter, Khoschy Schawkat, Anton S. Becker, Olivio Donati, Ender Konukoglu:
PHiSeg: Capturing Uncertainty in Medical Image Segmentation. CoRR abs/1906.04045 (2019) - 2018
- [c6]Yigit Baran Can, Krishna Chaitanya, Basil Mustafa, Lisa M. Koch, Ender Konukoglu, Christian F. Baumgartner:
Learning to Segment Medical Images with Scribble-Supervision Alone. DLMIA/ML-CDS@MICCAI 2018: 236-244 - [c5]Neerav Karani, Krishna Chaitanya, Christian F. Baumgartner, Ender Konukoglu:
A Lifelong Learning Approach to Brain MR Segmentation Across Scanners and Protocols. MICCAI (1) 2018: 476-484 - [i3]Neerav Karani, Krishna Chaitanya, Christian F. Baumgartner, Ender Konukoglu:
A Lifelong Learning Approach to Brain MR Segmentation Across Scanners and Protocols. CoRR abs/1805.10170 (2018) - [i2]Yigit Baran Can, Krishna Chaitanya, Basil Mustafa, Lisa M. Koch, Ender Konukoglu, Christian F. Baumgartner:
Learning to Segment Medical Images with Scribble-Supervision Alone. CoRR abs/1807.04668 (2018) - [i1]Timon Elmer, Krishna Chaitanya, Prateek Purwar, Christoph Stadtfeld:
The validity of RFID badges measuring face-to-face interactions. CoRR abs/1811.12189 (2018) - 2017
- [c4]Akash Agrawall, Krishna Chaitanya, Arnav Kumar Agrawal, Venkatesh Choppella:
Mitigating Browser-based DDoS Attacks using CORP. ISEC 2017: 137-146 - 2015
- [c3]Gourinath Banda, Krishna Chaitanya, Harsh Mohan:
An IoT Protocol and Framework for OEMs to Make IoT-Enabled Devices forward Compatible. SITIS 2015: 824-832 - 2010
- [c2]C. Sudeep Reddy, Harshita Nanduri, P. D. S. R. Sandeep, Krishna Chaitanya, K. S. Rajan:
GEO-News: A Geo-Hierarchy based News Search and Extraction. NTCIR 2010: 192-198
2000 – 2009
- 2008
- [c1]Krishna Chaitanya, Rohit Sinha:
Energy and entropy based switching algorithm for speech endpoint detection in varying SNR conditions. INTERSPEECH 2008: 2578-2581
Coauthor Index
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