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Noisy Label Processing for Classification: A Survey
April 8, 2024, 4:44 a.m. | Mengting Li, Chuang Zhu
cs.CV updates on arXiv.org arxiv.org
Abstract: In recent years, deep neural networks (DNNs) have gained remarkable achievement in computer vision tasks, and the success of DNNs often depends greatly on the richness of data. However, the acquisition process of data and high-quality ground truth requires a lot of manpower and money. In the long, tedious process of data annotation, annotators are prone to make mistakes, resulting in incorrect labels of images, i.e., noisy labels. The emergence of noisy labels is inevitable. …
abstract achievement acquisition arxiv classification computer computer vision cs.ai cs.cv data however money networks neural networks process processing quality success survey tasks truth type vision
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