Few-Shot Fine-Grained Image Classification: A Comprehensive Review
Jie Ren,
Changmiao Li,
Yaohui An
et al.
Abstract:Few-shot fine-grained image classification (FSFGIC) methods refer to the classification of images (e.g., birds, flowers, and airplanes) belonging to different subclasses of the same species by a small number of labeled samples. Through feature representation learning, FSFGIC methods can make better use of limited sample information, learn more discriminative feature representations, greatly improve the classification accuracy and generalization ability, and thus achieve better results in FSFGIC tasks. In this … Show more
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