The invention provides a leaf vegetable
disease detection, regulation and control method and
system based on
deep learning. And collecting a growth image and environmental parameter data of the
leafy vegetables, performing
disease detection by using the improved DETR model, and outputting a bounding box and a
disease category of a
disease area. Segmenting by adopting a weak supervision segmentation method based on a bounding box to obtain a pixel-level segmentation map of each disease region, extracting color, shape and area characteristics of the disease regions, and carrying out grading quantification on the diseases to generate a disease grade
score. The optimal planting strategy is obtained through the deep Q
network model, the environment parameters such as illumination, temperature and
humidity are adjusted through the execution mechanism, the leaf vegetable growth environment is optimized, and the production efficiency is improved. According to the method,
deep learning and intelligent regulation and control technologies are combined, efficient disease recognition and fine environment regulation and control can be achieved, loss caused by diseases is reduced, the yield and quality of
leafy vegetables are improved, manual intervention is reduced, and the method has high practicability and popularization value.