Method and system for identifying trapped insects in air based on convolutional neural network

The invention provides an air trapped insect identification method and system based on a convolutional neural network. The method comprises the steps of 1, making a data set of under-lamp insect images; 2, preprocessing the data set, and dividing the data set into a training set, a verification set and a test set; step 3, generating an annotation file; 4, constructing an insect identification and classification model based on YOLO V8, and training by using the training set; 5, verifying the trained insect identification and classification model through a verification set, and testing through a test set; and step 6, classifying and identifying the insects trapped by the high-altitude lamp by using the insect identification and classification model passing the test. According to the method, a traditional convolution block attention module is improved, and a feature attention module is added; an insect identification and classification model is constructed based on YOLO V8, and an improved convolutional block at