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A Semi-Supervised Two-Stage Approach to Learning from Noisy Labels

8 February 2018

Papers citing "A Semi-Supervised Two-Stage Approach to Learning from Noisy Labels"

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Title
Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Erjian Guo Zicheng Wang Zhen Zhao Luping Zhou NoLa 170 1 0 12 Jan 2025
SURE: SUrvey REcipes for building reliable and robust deep networks Yuting Li Yingyi Chen Xuanlong Yu Dexiong Chen Xi Shen UQCV OOD 85 4 0 01 Mar 2024
Class Prototype-based Cleaner for Label Noise Learning Jingjia Huang Yuanqi Chen Jiashi Feng Xinglong Wu NoLa SSL 57 0 0 21 Dec 2022
SplitNet: Learnable Clean-Noisy Label Splitting for Learning with Noisy Labels Daehwan Kim Kwang-seok Ryoo Hansang Cho Seung Wook Kim NoLa 84 4 0 20 Nov 2022
SelfMix: Robust Learning Against Textual Label Noise with Self-Mixup Training Dan Qiao Chenchen Dai Yuyang Ding Juntao Li Qiang Chen Wenliang Chen Hao Fei VLM NoLa 78 10 0 10 Oct 2022
Jigsaw-ViT: Learning Jigsaw Puzzles in Vision Transformer Yingyi Chen Xiaoke Shen Yahui Liu Qinghua Tao Johan A. K. Suykens AAML ViT 85 24 0 25 Jul 2022
Compressing Features for Learning with Noisy Labels Yingyi Chen S. Hu Xin Shen C. Ai Johan A. K. Suykens NoLa 73 14 0 27 Jun 2022
Deep Learning with Label Noise: A Hierarchical Approach Li-Wei Chen Ningyuan Huang Cong Mu Hayden S. Helm Kate Lytvynets Weiwei Yang Carey E. Priebe NoLa 77 1 0 28 May 2022
Robust Medical Image Classification from Noisy Labeled Data with Global and Local Representation Guided Co-training Cheng Xue Lequan Yu Pengfei Chen Qi Dou Pheng-Ann Heng NoLa 66 54 0 10 May 2022
UNICON: Combating Label Noise Through Uniform Selection and Contrastive Learning Nazmul Karim Mamshad Nayeem Rizve Nazanin Rahnavard Ajmal Mian M. Shah NoLa 89 100 0 28 Mar 2022
Semantic Clustering based Deduction Learning for Image Recognition and Classification Wenchi Ma Xuemin Tu Bo Luo Guanghui Wang 81 29 0 25 Dec 2021
Two Wrongs Don't Make a Right: Combating Confirmation Bias in Learning with Label Noise Mingcai Chen Hao Cheng Yuntao Du Ming Xu Wenyu Jiang Chongjun Wang NoLa 73 26 0 06 Dec 2021
Open-Vocabulary Instance Segmentation via Robust Cross-Modal Pseudo-Labeling Dat T. Huynh Jason Kuen Zhe Lin Jiuxiang Gu Ehsan Elhamifar ISeg VLM 109 86 0 24 Nov 2021
Addressing out-of-distribution label noise in webly-labelled data Paul Albert Diego Ortego Eric Arazo Noel E. O'Connor Kevin McGuinness NoLa 60 18 0 26 Oct 2021
PropMix: Hard Sample Filtering and Proportional MixUp for Learning with Noisy Labels F. Cordeiro Vasileios Belagiannis Ian Reid G. Carneiro NoLa 73 18 0 22 Oct 2021
Label Cleaning Multiple Instance Learning: Refining Coarse Annotations on Single Whole-Slide Images Zhenzhen Wang Carla Saoud A. Popel Aaron W. James Aleksander S. Popel Jeremias Sulam 87 23 0 22 Sep 2021
Learning Fast Sample Re-weighting Without Reward Data Zizhao Zhang Tomas Pfister 80 76 0 07 Sep 2021
Co-learning: Learning from Noisy Labels with Self-supervision Cheng Tan Jun Xia Lirong Wu Stan Z. Li NoLa 133 127 0 05 Aug 2021
Training Classifiers that are Universally Robust to All Label Noise Levels Jingyi Xu Tony Q.S. Quek Kai Fong Ernest Chong NoLa 58 2 0 27 May 2021
Generation and Analysis of Feature-Dependent Pseudo Noise for Training Deep Neural Networks Sree Ram Kamabattula Kumudha Musini Babak Namazi G. Sankaranarayanan V. Devarajan NoLa 18 0 0 22 May 2021
Boosting Semi-Supervised Face Recognition with Noise Robustness Yuchi Liu Hailin Shi Hang Du Rui Zhu Jun Wang Liang Zheng Tao Mei NoLa 52 19 0 10 May 2021
Boosting Co-teaching with Compression Regularization for Label Noise Yingyi Chen Xin Shen S. Hu Johan A. K. Suykens NoLa 83 47 0 28 Apr 2021
Joint Negative and Positive Learning for Noisy Labels Youngdong Kim Juseung Yun Hyounguk Shon Junmo Kim NoLa 76 63 0 14 Apr 2021
Industry Scale Semi-Supervised Learning for Natural Language Understanding Luoxin Chen Francisco Garcia Varun Kumar He Xie Jianhua Lu 38 7 0 29 Mar 2021
Co-matching: Combating Noisy Labels by Augmentation Anchoring Yangdi Lu Yang Bo Wenbo He NoLa 50 7 0 23 Mar 2021
On the Robustness of Monte Carlo Dropout Trained with Noisy Labels Purvi Goel Li Chen NoLa 72 15 0 22 Mar 2021
ScanMix: Learning from Severe Label Noise via Semantic Clustering and Semi-Supervised Learning Ragav Sachdeva F. Cordeiro Vasileios Belagiannis Ian Reid G. Carneiro 106 34 0 21 Mar 2021
LongReMix: Robust Learning with High Confidence Samples in a Noisy Label Environment F. Cordeiro Ragav Sachdeva Vasileios Belagiannis Ian Reid G. Carneiro NoLa 77 80 0 06 Mar 2021
DST: Data Selection and joint Training for Learning with Noisy Labels Yi Wei Xue Mei Xin Liu Pengxiang Xu NoLa 57 3 0 01 Mar 2021
How Does a Neural Network's Architecture Impact Its Robustness to Noisy Labels? Jingling Li Mozhi Zhang Keyulu Xu John P. Dickerson Jimmy Ba OOD NoLa 105 19 0 23 Dec 2020
Multi-Objective Interpolation Training for Robustness to Label Noise Diego Ortego Eric Arazo Paul Albert Noel E. O'Connor Kevin McGuinness NoLa 81 117 0 08 Dec 2020
SemiNLL: A Framework of Noisy-Label Learning by Semi-Supervised Learning Zhuowei Wang Jing Jiang Bo Han Lei Feng Bo An Gang Niu Guodong Long NoLa 81 17 0 02 Dec 2020
Using Under-trained Deep Ensembles to Learn Under Extreme Label Noise K. Nikolaidis T. Plagemann Stein Kristiansen V. Goebel Mohan Kankanhalli NoLa UQCV 78 3 0 23 Sep 2020
Reliable Label Bootstrapping for Semi-Supervised Learning Paul Albert Diego Ortego Eric Arazo Noel E. O'Connor Kevin McGuinness SSL 73 5 0 23 Jul 2020
Improving Object Detection with Selective Self-supervised Self-training Yandong Li Di Huang Danfeng Qin Liqiang Wang Boqing Gong 124 65 0 17 Jul 2020
Learning from Noisy Labels with Deep Neural Networks: A Survey Hwanjun Song Minseok Kim Dongmin Park Yooju Shin Jae-Gil Lee NoLa 136 1,009 0 16 Jul 2020
Meta Soft Label Generation for Noisy Labels G. Algan ilkay Ulusoy NoLa 86 38 0 11 Jul 2020
An Overview of Deep Semi-Supervised Learning Yassine Ouali C´eline Hudelot Myriam Tami SSL HAI 134 303 0 09 Jun 2020
Self-Learning with Rectification Strategy for Human Parsing Tao Li Zhiyuan Liang Sanyuan Zhao Jiahao Gong Jianbing Shen 74 35 0 17 Apr 2020
No Regret Sample Selection with Noisy Labels H. Song N. Mitsuo S. Uchida D. Suehiro NoLa 58 5 0 06 Mar 2020
DivideMix: Learning with Noisy Labels as Semi-supervised Learning Junnan Li R. Socher Guosheng Lin NoLa 139 1,036 0 18 Feb 2020
Towards Robust Learning with Different Label Noise Distributions Diego Ortego Eric Arazo Paul Albert Noel E. O'Connor Kevin McGuinness NoLa 55 25 0 18 Dec 2019
Image Classification with Deep Learning in the Presence of Noisy Labels: A Survey G. Algan ilkay Ulusoy NoLa VLM 96 334 0 11 Dec 2019
Deep learning with noisy labels: exploring techniques and remedies in medical image analysis Davood Karimi Haoran Dou Simon K. Warfield Ali Gholipour NoLa 133 551 0 05 Dec 2019
Distilling Effective Supervision from Severe Label Noise Zizhao Zhang Han Zhang Sercan O. Arik Honglak Lee Tomas Pfister NoLa 39 2 0 01 Oct 2019
NLNL: Negative Learning for Noisy Labels Youngdong Kim Junho Yim Juseung Yun Junmo Kim NoLa 63 277 0 19 Aug 2019
Deep Self-Learning From Noisy Labels Jiangfan Han Ping Luo Xiaogang Wang NoLa 98 282 0 06 Aug 2019
Unsupervised Label Noise Modeling and Loss Correction Eric Arazo Sanchez Diego Ortego Paul Albert Noel E. O'Connor Kevin McGuinness NoLa 149 618 0 25 Apr 2019
A Large RGB-D Dataset for Semi-supervised Monocular Depth Estimation Jaehoon Cho Dongbo Min Youngjung Kim Kwanghoon Sohn MDE 3DV 139 48 0 23 Apr 2019
An Entropic Optimal Transport Loss for Learning Deep Neural Networks under Label Noise in Remote Sensing Images B. Damodaran Rémi Flamary Vivien Seguy Nicolas Courty NoLa 70 40 0 02 Oct 2018