ABHFA-Net is a novel few-shot classification framework that models prototypes as distributions, applies spatial-channel attention, and uses Bhattacharyya-based contrastive loss, achieving state-of-the-art accuracies on benchmark and disaster datasets.
Advances in neural informatio n processing systems 35, 35504–35518 (2022)
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Enhancing Few-Shot Classification of Benchmark and Disaster Imagery with ABHFA-Net
ABHFA-Net is a novel few-shot classification framework that models prototypes as distributions, applies spatial-channel attention, and uses Bhattacharyya-based contrastive loss, achieving state-of-the-art accuracies on benchmark and disaster datasets.