Benchmarking the Robustness of Deep Neural Networks to Common Corruptions in Digital Pathology

30 June 2022

Yuxuan Sun

Papers citing "Benchmarking the Robustness of Deep Neural Networks to Common Corruptions in Digital Pathology"

22 / 22 papers shown

Title
Are Transformers More Robust Than CNNs? Yutong Bai Jieru Mei Alan Yuille Cihang Xie ViT AAML 240 263 0 10 Nov 2021
Benchmarks for Corruption Invariant Person Re-identification Minghui Chen Zhiqiang Wang Feng Zheng 51 26 0 01 Nov 2021
When Human Pose Estimation Meets Robustness: Adversarial Algorithms and Benchmarks Jiahang Wang Sheng Jin Wentao Liu Weizhong Liu Chao Qian Ping Luo AAML 52 58 0 13 May 2021
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows Ze Liu Yutong Lin Yue Cao Han Hu Yixuan Wei Zheng Zhang Stephen Lin B. Guo ViT 441 21,418 0 25 Mar 2021
Learning domain-agnostic visual representation for computational pathology using medically-irrelevant style transfer augmentation R. Yamashita J. Long Snikitha Banda Jeanne Shen D. Rubin OOD MedIm 34 50 0 02 Feb 2021
Training data-efficient image transformers & distillation through attention Hugo Touvron Matthieu Cord Matthijs Douze Francisco Massa Alexandre Sablayrolles Hervé Jégou ViT 377 6,762 0 23 Dec 2020
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale Alexey Dosovitskiy Lucas Beyer Alexander Kolesnikov Dirk Weissenborn Xiaohua Zhai ... Matthias Minderer G. Heigold Sylvain Gelly Jakob Uszkoreit N. Houlsby ViT 637 41,003 0 22 Oct 2020
Benchmarking the Robustness of Semantic Segmentation Models Christoph Kamann Carsten Rother VLM UQCV 50 165 0 14 Aug 2019
Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming Claudio Michaelis Benjamin Mitzkus Robert Geirhos E. Rusak Oliver Bringmann Alexander S. Ecker Matthias Bethge Wieland Brendel 3DPC 95 445 0 17 Jul 2019
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks Mingxing Tan Quoc V. Le 3DV MedIm 137 18,115 0 28 May 2019
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations Dan Hendrycks Thomas G. Dietterich OOD VLM 170 3,431 0 28 Mar 2019
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness Robert Geirhos Patricia Rubisch Claudio Michaelis Matthias Bethge Felix Wichmann Wieland Brendel 100 2,668 0 29 Nov 2018
Rotation Equivariant CNNs for Digital Pathology Bastiaan S. Veeling J. Linmans Jim Winkens Taco S. Cohen Max Welling 109 583 0 08 Jun 2018
Why do deep convolutional networks generalize so poorly to small image transformations? Aharon Azulay Yair Weiss 70 560 0 30 May 2018
MobileNetV2: Inverted Residuals and Linear Bottlenecks Mark Sandler Andrew G. Howard Menglong Zhu A. Zhmoginov Liang-Chieh Chen 178 19,271 0 13 Jan 2018
ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices Xiangyu Zhang Xinyu Zhou Mengxiao Lin Jian Sun AI4TS 138 6,867 0 04 Jul 2017
On Calibration of Modern Neural Networks Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger UQCV 299 5,827 0 14 Jun 2017
Understanding How Image Quality Affects Deep Neural Networks Samuel F. Dodge Lina Karam VLM 65 729 0 14 Apr 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 193,878 0 10 Dec 2015
U-Net: Convolutional Networks for Biomedical Image Segmentation Olaf Ronneberger Philipp Fischer Thomas Brox SSeg 3DV 1.8K 77,133 0 18 May 2015
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.6K 100,348 0 04 Sep 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 270 14,918 1 21 Dec 2013