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.
· Italian National Conference... · 0 citations