The invention discloses a leaf
nutrition state diagnosis and chemical
fertilizer adjustment method based on image recognition. The method comprises the following steps: S1, collecting a leaf image; s2, performing denoising, enhancement and background removal on the image, extracting color, shape and texture features, and generating a leaf
feature vector; s3, modeling by using a nonlinear dynamic
chaotic system, detecting abnormal changes, and performing multi-scale
chaotic analysis; s4, constructing a topological network for high-dimensional topological
data analysis, and performing multi-
modal data fusion in combination with a
Bayesian network; s5, dynamically adjusting
algorithm parameters according to a fusion result; s6, generating a diagnosis result through a
generative adversarial network,
image fusion and a deep artifact removal
algorithm; and S7, constructing a cognitive
intelligent agent and group intelligence optimization
algorithm, and carrying out dynamic environment
adaptation and closed-loop
feedback regulation and control. According to the invention, the efficiency and accuracy of
nutrition state diagnosis are improved, the
fertilizer application is optimized, and the environmental
pollution is reduced.