Learning from noisy labels with deep neural networks: A survey
Deep learning has achieved remarkable success in numerous domains with help from large
amounts of big data. However, the quality of data labels is a concern because of the lack of …
amounts of big data. However, the quality of data labels is a concern because of the lack of …
Source-free unsupervised domain adaptation: A survey
Unsupervised domain adaptation (UDA) via deep learning has attracted appealing attention
for tackling domain-shift problems caused by distribution discrepancy across different …
for tackling domain-shift problems caused by distribution discrepancy across different …
Dividemix: Learning with noisy labels as semi-supervised learning
Learn from all: Erasing attention consistency for noisy label facial expression recognition
Abstract Noisy label Facial Expression Recognition (FER) is more challenging than
traditional noisy label classification tasks due to the inter-class similarity and the annotation …
traditional noisy label classification tasks due to the inter-class similarity and the annotation …