Abstract：Crop disease and insect pest is one of the important issue facing agricultural production．It is of important significance to ensure the quality safety of agricultural products and improve economic benefits by rapid and effective identification of crop disease and insect pest．In recent years，the image-based automatic diagnosis technology of crop disease and pest has been widely studied and a series of progress has been made．This paper mainly analyzed the current development status of automatic identification technology for crop disease and pest in China；expounded the key technology and implementation steps of using convolution neural network to establish the identification model of disease and pest；introduced the current mainstream deep learning model algorithms and idea improvement for image recognition；and analyzed the existing technical bottlenecks and development trends，hoping to provide references for the application of image recognition technology in actual production．
王明，张倩. 我国基于深度学习的图像识别技术在农作物病虫害识别中的研究进展[J]. 中国蔬菜, 2023, 1(3): 22-28.
WANG Ming，ZHANG Qian. Research Progress of Image Recognition Technology Based on Depth Learning in Identification of Pest and Disease in Crops in China. China Vegetables, 2023, 1(3): 22-28.
