Research on Crop Leaf Disease Recognition Algorithm Based on Embedded Device

Crop diseases seriously threaten crop yields, and timely detection and identification of these diseases and corresponding measures can effectively reduce this threat. With the help of embedded devices, it is possible to detect whether crops are diseased and to study recognition algorithms for more accurate identification. This paper combines machine vision technology with embedded devices to achieve rapid detection and localization through the YOLOV2 algorithm. A disease recognition system is constructed by connecting the model with a camera and display screen, and its accuracy and practicality are verified through actual testing. This algorithm can effectively identify crop leaf diseases, providing a new agricultural disease prevention and control solution.