Cotton aphid pest monitoring method and system based on spectral imaging and deep learning

The invention discloses a cotton aphid insect pest monitoring method and system based on spectral imaging and deep learning, and relates to the technical field of insect pest condition monitoring. A hyperspectral imaging system is utilized to obtain hyperspectral images of cotton leaves, a single cotton leaf is used as a region of interest, the hyperspectral images of the single leaves are extracted, and finally an average spectrum and a first-order derivative spectrum are calculated. Spectral information and a deep learning technology are fully utilized, the importance of each waveband is discovered by using a visualization technology, and important wavebands are selected for monitoring and early warning; a three-dimensional convolutional neural network is used for learning a hyperspectral image of a single leaf, the hyperspectral image in a visible light and near-infrared band range is selected, a saliency map is generated by using a visualization technology, and a cotton leaf damagepart stressed by cotton aphids can be found. Whether cotton plants are stressed by cotton aphid pests or not can be rapidly monitored.