Dynamic deep multi-label image data augmentation based on self-paced learning

doi:10.1016/j.cviu.2025.104530

2025-10-14

PRE

DOI：10.1016/j.cviu.2025.104530

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摘要

En 中文

• 端到端框架通过自适应增强改进多标签分类。• 自定步长学习选择简单样本以指导训练过程中的增强。• 图像数据合成减少自定步长选择的样本中的类别不平衡。• 噪声缓解过滤低相似度样本以提升训练质量。

期刊

Computer Vision and Image Understanding

IF:

3.5

论文数:

555

被引数:

7.3K

机构

Shanxi University

学者数:

1.3W

论文数: 8.4K

被引数: 1.2W

Xidian University

学者数:

2.4W

论文数: 1.9W

被引数: 9.7K

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