EfficientNetB5 with CBAM reaches 93.3% accuracy on a 1,366-image peach leaf damage dataset and EfficientNetB3 with CBAM reaches 93% macro F1 after transfer to a 180-image local domain.
YOLO-light-pruned: A lightweight model for monitoring maize seedling count and leaf age using near-ground and UAV RGB images
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Attention mechanisms and transfer learning for robust peach leaf damage classification under domain shift
EfficientNetB5 with CBAM reaches 93.3% accuracy on a 1,366-image peach leaf damage dataset and EfficientNetB3 with CBAM reaches 93% macro F1 after transfer to a 180-image local domain.