Image classification method based on lightweight residual network

The invention discloses an image classification method based on a lightweight residual network, and mainly solves the problems of excessive network model parameters and insufficient utilization of image feature information of the existing image classification method. The implementation scheme is as follows: obtaining a training sample set and a test sample set; changing a traditional residual unit, establishing five different lightweight unit blocks, and sequentially cascading the five different lightweight unit blocks with a full connection layer and a classifier to form a lightweight residual network image classification model; training the constructed image classification model by using the training sample set and adopting a back propagation algorithm; and inputting the test sample set into the trained lightweight residual network image classification model to obtain a classification result. According to the method, high image classification accuracy can be obtained in an image classification task, the net