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Learning with noisy labels for robust fatigue detection

Knowledge-based systems, 2024-09, Vol.300, p.112199, Article 112199

2024

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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

Visual computing for industry, biomedicine and art, 2024-05, Vol.7 (1), p.10-10, Article 10

2024

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ANNE: Adaptive Nearest Neighbours and Eigenvector-based sample selection for robust learning with noisy labels

Pattern recognition, 2025-03, Vol.159, p.111132, Article 111132

2025

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Delving Deep Into Label Smoothing

IEEE transactions on image processing, 2021, Vol.30, p.5984-5996

2021

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Intelligent fault diagnosis of rolling bearing based on wavelet transform and improved ResNet under noisy labels and environment

Engineering applications of artificial intelligence, 2022-10, Vol.115, p.105269, Article 105269

2022

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Noise-robust Vision-language Pre-training with Positive-negative Learning

IEEE transactions on pattern analysis and machine intelligence, 2024-09, Vol.PP, p.1-13

2024

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Multi-label noisy samples in underwater inspection from the oil and gas industry

Neural computing & applications, 2024-04, Vol.36 (12), p.6855-6873

2024

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Learning From Noisy Labels With Deep Neural Networks: A Survey

IEEE transaction on neural networks and learning systems, 2023-11, Vol.34 (11), p.8135-8153

2023

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A fault diagnosis method for wind turbines gearbox based on adaptive loss weighted meta-ResNet under noisy labels

Mechanical systems and signal processing, 2021-12, Vol.161, p.107963, Article 107963

2021

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Toward high-quality pseudo masks from noisy or weak annotations for robust medical image segmentation

Neural networks, 2025-01, Vol.181, p.106850, Article 106850

2025

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ArcFace: Additive Angular Margin Loss for Deep Face Recognition

IEEE transactions on pattern analysis and machine intelligence, 2022-10, Vol.44 (10), p.5962-5979

2022

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Noisy label based discriminative least squares regression and its kernel extension for object identification

KSII transactions on Internet and information systems, 2017-05, Vol.11 (5), p.2523-2538

2017

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Large-Scale Object Detection in the Wild With Imbalanced Data Distribution, and Multi-Labels

IEEE transactions on pattern analysis and machine intelligence, 2024-12, Vol.46 (12), p.9255-9271

2024

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Extended T: Learning With Mixed Closed-Set and Open-Set Noisy Labels

IEEE transactions on pattern analysis and machine intelligence, 2023-03, Vol.45 (3), p.3047-3058

2023

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Accurate water extraction using remote sensing imagery based on normalized difference water index and unsupervised deep learning

Journal of hydrology (Amsterdam), 2022-09, Vol.612, p.128202, Article 128202

2022

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Subclass consistency regularization for learning with noisy labels based on contrastive learning

Neurocomputing (Amsterdam), 2025-01, Vol.614, p.128759, Article 128759

2025

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Decoding class dynamics in learning with noisy labels

Pattern recognition letters, 2024-08, Vol.184, p.239-245

2024

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Partial Multi-Label Learning With Noisy Label Identification

IEEE transactions on pattern analysis and machine intelligence, 2022-07, Vol.44 (7), p.3676-3687

2022

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P-DIFF+: Improving learning classifier with noisy labels by Noisy Negative Learning loss

Neural networks, 2021-12, Vol.144, p.1-10

2021

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CJC-net: A cyclical training method with joint loss and co-teaching strategy net for deep learning under noisy labels

Information sciences, 2021-11, Vol.579, p.186-198

2021

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A systematic review of generalization research in medical image classification

Computers in biology and medicine, 2024-12, Vol.183, p.109256, Article 109256

2024

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A Noise-Robust Framework for Automatic Segmentation of COVID-19 Pneumonia Lesions From CT Images

IEEE transactions on medical imaging, 2020-08, Vol.39 (8), p.2653-2663

2020

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Noisy label based discriminative least squares regression and its kernel extension for object identification

KSII Transactions on Internet and Information Systems, 2017, 11(5), , pp.2523-2538

2017

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Co-Learning Meets Stitch-Up for Noisy Multi-label Visual Recognition

IEEE transactions on image processing, 2023-01, Vol.32, p.1-1

2023

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CMW-Net: Learning a Class-Aware Sample Weighting Mapping for Robust Deep Learning

IEEE transactions on pattern analysis and machine intelligence, 2023-10, Vol.45 (10), p.11521-11539

2023

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Learning with noisy labels for robust fatigue detection

Typicality- and instance-dependent label noise-combating: a novel framework for simulating and combating real-world noisy labels for endoscopic polyp classification

ANNE: Adaptive Nearest Neighbours and Eigenvector-based sample selection for robust learning with noisy labels

Delving Deep Into Label Smoothing

Intelligent fault diagnosis of rolling bearing based on wavelet transform and improved ResNet under noisy labels and environment

Noise-robust Vision-language Pre-training with Positive-negative Learning

Multi-label noisy samples in underwater inspection from the oil and gas industry

Learning From Noisy Labels With Deep Neural Networks: A Survey

A fault diagnosis method for wind turbines gearbox based on adaptive loss weighted meta-ResNet under noisy labels

Toward high-quality pseudo masks from noisy or weak annotations for robust medical image segmentation

ArcFace: Additive Angular Margin Loss for Deep Face Recognition

Noisy label based discriminative least squares regression and its kernel extension for object identification

Large-Scale Object Detection in the Wild With Imbalanced Data Distribution, and Multi-Labels

Extended T: Learning With Mixed Closed-Set and Open-Set Noisy Labels

Accurate water extraction using remote sensing imagery based on normalized difference water index and unsupervised deep learning

Subclass consistency regularization for learning with noisy labels based on contrastive learning

Decoding class dynamics in learning with noisy labels

Partial Multi-Label Learning With Noisy Label Identification

P-DIFF+: Improving learning classifier with noisy labels by Noisy Negative Learning loss

CJC-net: A cyclical training method with joint loss and co-teaching strategy net for deep learning under noisy labels

A systematic review of generalization research in medical image classification

A Noise-Robust Framework for Automatic Segmentation of COVID-19 Pneumonia Lesions From CT Images

Noisy label based discriminative least squares regression and its kernel extension for object identification

Co-Learning Meets Stitch-Up for Noisy Multi-label Visual Recognition

CMW-Net: Learning a Class-Aware Sample Weighting Mapping for Robust Deep Learning

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