Modeling and Correction of Label Noise Uncertainty for SAR ATR by Yue YU, Chen WANG, Jun SHI, Chongben TAO, Liang LI, Xinxin TANG, Liming ZHOU, Shunjun WEI, Xiaoling ZHANG

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A review on label cleaning techniques for learning with noisy labels by Jongmin Shin, Jonghyeon Won, Hyun-Suk Lee, Jang-Won Lee

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Human-Annotated Label Noise and Their Impact on ConvNets for Remote Sensing Image Scene Classification by Longkang Peng, Tao Wei, Xuehong Chen, Xiaobei Chen, Rui Sun, Luoma Wan, Jin Chen, Xiaolin Zhu

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Typicality- and instance-dependent label noise-combating: a novel framework for simulating and combating real-world noisy labels for endoscopic polyp classification by Yun Gao, Junhu Fu, Yuanyuan Wang, Yi Guo

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An Adaptive and Robust Method for Oriented Oversampling With Spatial Information for Imbalanced Noisy Datasets by Yi Deng, Mingyong Li

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Improving Building Extraction by Using Knowledge Distillation to Reduce the Impact of Label Noise by Gang Xu, Min Deng, Geng Sun, Ya Guo, Jie Chen

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Regularization Using Noise Samples Identified by the Feature Norm for Face Recognition by Taeseong Gim, Kyung-Ah Sohn

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Regularization in Network Optimization via Trimmed Stochastic Gradient Descent With Noisy Label by Kensuke Nakamura, Bong-Soo Sohn, Kyoung-Jae Won, Byung-Woo Hong

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Combating Label Noise in Image Data Using MultiNET Flexible Confident Learning by Adam Popowicz, Krystian Radlak, Slawomir Lasota, Karolina Szczepankiewicz, Michal Szczepankiewicz

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A reconstruction error-based framework for label noise detection by Zahra Salekshahrezaee, Joffrey L. Leevy, Taghi M. Khoshgoftaar

Subjects: “…Label noise…”
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Uncertainty is not sufficient for identifying noisy labels in training data for binary segmentation of building footprints by Hannah Ulman, Jonas Gütter, Julia Niebling

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Label Noise Cleaning with an Adaptive Ensemble Method Based on Noise Detection Metric by Wei Feng, Yinghui Quan, Gabriel Dauphin

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Learning Accurate Pseudo-Labels via Feature Similarity in the Presence of Label Noise by Peng Wang, Xiaoxiao Wang, Zhen Wang , Yongfeng Dong

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CoDC: Accurate Learning with Noisy Labels via Disagreement and Consistency by Yongfeng Dong, Jiawei Li, Zhen Wang, Wenyu Jia

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Noisy label relabeling by nonparallel support vector machine by A. Sahleh, M. Salahi

Subjects: “…label noise…”
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Agreement and Disagreement-Based Co-Learning with Dual Network for Hyperspectral Image Classification with Noisy Labels by Youqiang Zhang, Jin Sun, Hao Shi, Zixian Ge, Qiqiong Yu, Guo Cao, Xuesong Li

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An Ensemble and Iterative Recovery Strategy Based <i>k</i>GNN Method to Edit Data with Label Noise by Baiyun Chen, Longhai Huang, Zizhong Chen, Guoyin Wang

Subjects: “…label noise…”
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Leveraging Expert Knowledge for Label Noise Mitigation in Machine Learning by Quoc Nguyen, Tomoaki Shikina, Daichi Teruya, Seiji Hotta, Huy-Dung Han, Hironori Nakajo

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FARMSAR: Fixing AgRicultural Mislabels Using Sentinel-1 Time Series and AutoencodeRs by Thomas Di Martino, Régis Guinvarc’h, Laetitia Thirion-Lefevre, Elise Colin

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On the Suitability of Bagging-Based Ensembles with Borderline Label Noise by José A. Sáez, José L. Romero-Béjar

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