Frontiers in Plant Science • Vol 15
Efficient and accurate identification of maize rust disease using deep learning model
February 2025 • Pei Wang, Jiajia Tan, Yuheng Yang, Tong Zhang, Pengxin Wu, Xinglong Tang, Hui Li, Xiongkui He, Xinping Chen
Common corn rust and southern corn rust, two typical maize diseases during growth stages, require accurate differentiation to understand their occurrence patterns and pathogenic risks. To address this, a specialized Maize-Rust model integrating a SimAM module in the YOLOv8s backbone and a BiFPN for scale fusion, along with a DWConv for streamlined detection, was developed. The model achieved an accuracy of 94.6%, average accuracy of 91.6%, recall rate of 85.4%, and F1 value of 0.823, outperforming Faster-RCNN and …