Segmentation with Noisy Labels via Spatially Correlated Distributions

21 April 2025

Papers citing "Segmentation with Noisy Labels via Spatially Correlated Distributions"

21 / 21 papers shown

Title
Impact of imperfect annotations on CNN training and performance for instance segmentation and classification in digital pathology Laura Gálvez Jiménez Christine Decaestecker 70 1 0 18 Oct 2024
AIO2: Online Correction of Object Labels for Deep Learning with Incomplete Annotation in Remote Sensing Image Segmentation Chenying Liu C. Albrecht Yi Wang Qingyu Li Xiao Xiang Zhu VLM 76 10 0 03 Mar 2024
Learning to Segment from Noisy Annotations: A Spatial Correction Approach Jiacheng Yao Yikai Zhang Songzhu Zheng Mayank Goswami Prateek Prasanna Chao Chen 83 15 0 21 Jul 2023
Robust T-Loss for Medical Image Segmentation Alvaro Gonzalez-Jimenez Simone Lionetti Philippe Gottfrois Fabian Gröger Marc Pouly Alexander A. Navarini OOD 109 11 0 01 Jun 2023
OpenEarthMap: A Benchmark Dataset for Global High-Resolution Land Cover Mapping J. Xia Naoto Yokoya B. Adriano Clifford Broni-Bediako VLM 85 73 0 19 Oct 2022
Labeling instructions matter in biomedical image analysis Tim Radsch Annika Reinke V. Weru M. Tizabi Nicholas Schreck A. Emre Kavur Bunyamin Pekdemir T. Ross A. Kopp-Schneider Lena Maier-Hein 74 56 0 20 Jul 2022
Adaptive Early-Learning Correction for Segmentation from Noisy Annotations Sheng Liu Kangning Liu Weicheng Zhu Yiqiu Shen C. Fernandez‐Granda NoLa 110 106 0 07 Oct 2021
Superpixel-guided Iterative Learning from Noisy Labels for Medical Image Segmentation Shuailin Li Zhitong Gao Xuming He NoLa 64 27 0 21 Jul 2021
Distilling effective supervision for robust medical image segmentation with noisy labels Jialin Shi Ji Wu NoLa 55 32 0 21 Jun 2021
Cascaded Robust Learning at Imperfect Labels for Chest X-ray Segmentation Cheng Xue Q. Deng Xuelong Li Qi Dou Pheng Ann Heng 65 27 0 05 Apr 2021
Disentangling Human Error from the Ground Truth in Segmentation of Medical Images Le Zhang Ryutaro Tanno Moucheng Xu Chen Jin Joseph Jacob O. Ciccarelli F. Barkhof Daniel C. Alexander NoLa 84 101 0 31 Jul 2020
Combating noisy labels by agreement: A joint training method with co-regularization Hongxin Wei Lei Feng Xiangyu Chen Bo An NoLa 368 522 0 05 Mar 2020
Confidence Scores Make Instance-dependent Label-noise Learning Possible Antonin Berthon Bo Han Gang Niu Tongliang Liu Masashi Sugiyama NoLa 109 108 0 11 Jan 2020
Classification of Large-Scale High-Resolution SAR Images with Deep Transfer Learning Zhongling Huang C. Dumitru Zongxu Pan Bin Lei Mihai Datcu 65 88 0 06 Jan 2020
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks Mingxing Tan Quoc V. Le 3DV MedIm 209 18,224 0 28 May 2019
Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels Bo Han Quanming Yao Xingrui Yu Gang Niu Miao Xu Weihua Hu Ivor Tsang Masashi Sugiyama NoLa 132 2,085 0 18 Apr 2018
Making Deep Neural Networks Robust to Label Noise: a Loss Correction Approach Giorgio Patrini A. Rozza A. Menon Richard Nock Zhuang Li NoLa 129 1,460 0 13 Sep 2016
Variational Inference: A Review for Statisticians David M. Blei A. Kucukelbir Jon D. McAuliffe BDL 340 4,817 0 04 Jan 2016
U-Net: Convolutional Networks for Biomedical Image Segmentation Olaf Ronneberger Philipp Fischer Thomas Brox SSeg 3DV 1.9K 77,520 0 18 May 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.2K 150,433 0 22 Dec 2014
An Empirical Study into Annotator Agreement, Ground Truth Estimation, and Algorithm Evaluation T. Lampert André Stumpf P. Gançarski 84 89 0 01 Jul 2013