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ConCA: Concentration-Aware Channel Attention for Fine-Grained Visual Recognition
Lightweight channel attention mechanisms are widely used in image classification, yet their effectiveness in fine-grained visual recognition (FGVR) remains limited. Most modules summarize each channel by global average pooling (GAP), which captures activation magnitude but ignores spatial concentrat
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