LiNC: Lightweight Noise Correction via per-sample trust and Gaussian mixture modeling
Read the original at arxiv.org→arXiv:2608.04147v1 Announce Type: new Abstract: Label noise is common in medical imaging datasets due to factors such as inter-rater variability, annotation errors, and ambiguous cases. This can severely undermine...
Original headline: "LiNC: Lightweight Noise Correction via Per-Sample Trust and Gaussian Mixture Modeling"
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- Aug 6, 04:00 UTC arXiv cs.LG lead source LiNC: Lightweight Noise Correction via Per-Sample Trust and Gaussian Mixture Modeling