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Cheng-Yun Liu

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Open access Sep 2026

IFMA-Net: Interactive Feature Modulated Attention Network for Accurate Identification of Cotton Pests and Diseases from Field Images

IFMA-Net’s potential for accurate pest and disease identification in practical agricultural sensing scenarios is demonstrated and perturbation experiments showed higher retention than ResNet-50 under random occlusion but substantial degradation under severe Gaussian noise.

Li-Li Song, Zhen-Xue Chen, Cheng-Yun Liu et al. · 0 citations

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