Application of improved MobileNetV3 in agricultural disease and pest recognition
Kai Wang · 2024
Agricultural diseases and pests pose a formidable menace to crop production and the safety of agricultural products. To address the pressing need for rapid and accurate identification and detection of these agricultural threats, this study presents novel model enhancements to the MobileNetV3 network architecture specifically designed for discerning specific agricultural diseases and pests. The refined network structure capitalizes on the utilization of multi-level feature information extracted from images, thereby bolstering the precision and robustness of agricultural disease and pest recognition. The proposed methodology exhibits outstanding performance in agricultural disease and pest recognition tasks, indicating its strong potential for practical applications.