STA-Net, a 401K-parameter model with a decoupled shape-texture attention module, reaches 89.00% accuracy and 88.96% F1 on the CCMT plant disease dataset.
Ccmt-9: A public dataset for crop classification and disease detection in cashew, cassava, maize, and tomato
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STA-Net: A Decoupled Shape and Texture Attention Network for Lightweight Plant Disease Classification
STA-Net, a 401K-parameter model with a decoupled shape-texture attention module, reaches 89.00% accuracy and 88.96% F1 on the CCMT plant disease dataset.