Assessing and Enhancing Robustness of Deep Learning Models with Corruption Emulation in Digital Pathology

31 October 2023

Papers citing "Assessing and Enhancing Robustness of Deep Learning Models with Corruption Emulation in Digital Pathology"

8 / 8 papers shown

Title
PathInsight: Instruction Tuning of Multimodal Datasets and Models for Intelligence Assisted Diagnosis in Histopathology Xiaomin Wu Rui Xu Pengchen Wei Wenkang Qin Peixiang Huang Ziheng Li Lin Luo LM&MA 44 4 0 13 Aug 2024
MedMNIST-C: Comprehensive benchmark and improved classifier robustness by simulating realistic image corruptions Francesco Di Salvo Sebastian Doerrich Christian Ledig OOD 24 2 0 25 Jun 2024
Improving Vision-and-Language Reasoning via Spatial Relations Modeling Cheng Yang Rui Xu Ye Guo Peixiang Huang Yiru Chen Wenkui Ding Zhongyuan Wang Hong Zhou LRM 23 5 0 09 Nov 2023
SCAAT: Improving Neural Network Interpretability via Saliency Constrained Adaptive Adversarial Training Rui Xu Wenkang Qin Peixiang Huang Hao Wang Lin Luo FAtt AAML 28 2 0 09 Nov 2023
Benchmarking the Robustness of Deep Neural Networks to Common Corruptions in Digital Pathology Yunlong Zhang Yuxuan Sun Honglin Li S. Zheng Chenglu Zhu L. Yang OOD 62 27 0 30 Jun 2022
Gradient Matching for Domain Generalization Yuge Shi Jeffrey S. Seely Philip Torr Siddharth Narayanaswamy Awni Y. Hannun Nicolas Usunier Gabriel Synnaeve OOD 221 292 0 20 Apr 2021
Densely Connected Convolutional Networks Gao Huang Zhuang Liu L. V. D. van der Maaten Kilian Q. Weinberger PINN 3DV 315 36,381 0 25 Aug 2016
U-Net: Convolutional Networks for Biomedical Image Segmentation Olaf Ronneberger Philipp Fischer Thomas Brox SSeg 3DV 345 75,888 0 18 May 2015