Weakly Supervised Semantic and Attentive Data Mixing Augmentation for Fine-Grained Visual Categorization
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DOI: 10.1109/access.2022.3163302
Abstract: As a key factor, the availability of large-scale training samples determines the improvement of visual performance. However, the size of Fine-Grained Visual Categorization (FGVC) datasets is always limited. Therefore, overfitting as an issue in FGVC-related… read more here.
Keywords: data mixing; training samples; training; mixing augmentation ... See more keywords