398 citations · 401 across the 3 of their papers we have counts for
3 papers
cs.LG2026
Robust Self-Training with Closed-loop Label Correction for Learning from Noisy Labels
Zhanhui Lin, Yanlin Liu, Sanping Zhou
Training deep neural networks with noisy labels remains a significant challenge, often leading to degraded performance. Existing methods for handling label noise typically rely on…
cs.CV2021★ 3 cited
Progressive Depth Learning for Single Image Dehazing
Yudong Liang, Bin Wang, Jiaying Liu +3
The formulation of the hazy image is mainly dominated by the reflected lights and ambient airlight. Existing dehazing methods often ignore the depth cues and fail in distant areas…
cs.LG2019★ 398 cited
Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting
Jun Shu, Qi Xie, Lixuan Yi +4
Current deep neural networks (DNNs) can easily overfit to biased training data with corrupted labels or class imbalance. Sample re-weighting strategy is commonly used to alleviate…