Learning with noisy labels for robust fatigue detection
M Wang, R Hu, X Zhu, D Zhu, X Wang - Knowledge-Based Systems, 2024 - Elsevier
Fatigue is a significant safety concern across various domains, and accurate detection is
vital. However, the commonly employed fine-grained labels (seconds-based) frequently …
vital. However, the commonly employed fine-grained labels (seconds-based) frequently …
Dynamic training for handling textual label noise
Label noise causes deep neural networks to gradually memorize incorrect labels, leading to
a decline in generalization. In this paper, based on three observations from learning …
a decline in generalization. In this paper, based on three observations from learning …
A Noisy Sample Selection Framework Based on a Mixup Loss and Recalibration Strategy
Q Zhang, D Yu, X Zhou, H Gong, Z Li, Y Liu… - …, 2024 - search.proquest.com
Deep neural networks (DNNs) have achieved breakthrough progress in various fields,
largely owing to the support of large-scale datasets with manually annotated labels …
largely owing to the support of large-scale datasets with manually annotated labels …