Negative Pseudo Labeling using Class Proportion for Semantic Segmentation in Pathology

16 July 2020

Papers citing "Negative Pseudo Labeling using Class Proportion for Semantic Segmentation in Pathology"

6 / 6 papers shown

Title
Proportion Estimation by Masked Learning from Label Proportion Takumi Okuo Kazuya Nishimura Hiroaki Ito Kazuhiro Terada Akihiko Yoshizawa Ryoma Bise 28 2 0 08 May 2024
PercentMatch: Percentile-based Dynamic Thresholding for Multi-Label Semi-Supervised Classification Jun Huang Alexander Huang Beatriz C. Guerra Yen-Yun Yu 31 4 0 30 Aug 2022
WSSS4LUAD: Grand Challenge on Weakly-supervised Tissue Semantic Segmentation for Lung Adenocarcinoma Chu Han Xipeng Pan Lixu Yan Huan Lin Bingbing Li ... Chengda Lu Xin Chen C. Liang Qingling Zhang Zaiyi Liu 33 28 0 13 Apr 2022
Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels Yuchao Wang Haochen Wang Yujun Shen Jingjing Fei Wei Li Guoqiang Jin Liwei Wu Rui Zhao Xinyi Le UQCV 30 331 0 08 Mar 2022
Multi-Layer Pseudo-Supervision for Histopathology Tissue Semantic Segmentation using Patch-level Classification Labels Chu Han Jiatai Lin Jinhai Mai Yi Wang Qingling Zhang ... Zeyan Xu Xiaomei Huang Guoqiang Han Chang-xiu Liang Zaiyi Liu 32 89 0 14 Oct 2021
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results Antti Tarvainen Harri Valpola OOD MoMe 270 1,275 0 06 Mar 2017