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May 31, 2023 · To address IDN, Label Noise Learning (LNL) incorporates a sample selection stage to differentiate clean and noisy-label samples. This stage uses ...
This paper addresses this research gap by proposing a new noisy-label learning graphical model that can easily accommodate state-of-the-art (SOTA) noisy-label ...
Dec 23, 2023 · In this paper, we introduce a novel noise-robust learning method which integrates noise rate estimation into sample selection approaches for handling noisy ...
To mitigate such issues for label noise detectors, we provide a novel yet simple detector frame- work, filtering noisy labels via their eigenvectors (FINE) ...
Among these baselines, CoT, CoT+, and CL are sample selection algorithms that require knowledge of noise rates.
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Jul 11, 2024 · This paper proposes a novel technique for sample selection with noise rate estimation in the context of medical image analysis.
1a, the new sample selection approach based on the “manually provided” noise rate (dashed red curve) improves 6% in terms of prediction accuracy compared to the ...
Dec 23, 2023 · A new sample selection method that enhances the performance of neural networks when trained on noisy datasets by estimating the noise rate ...
Sep 30, 2024 · To address IDN, Label Noise Learning (LNL) incorporates a sample selection stage to differentiate clean and noisy-label samples. This stage uses ...
Nov 2, 2024 · A new sample selection methodology for noisy-label learning methods, leveraging the benefits of employing different sample selection strategies, ...
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