Abstract: In order to solve the problem of waste classification in university campus, a method of garbage image classification based on convolution neural network and normalization technology is proposed. Without complex processing of the input image, the network model can extract image features according to the
algorithm. By cooperating group normalization and each layer of the network model, the shortcomings of the traditional classification algorithm can be overcome and the garbage image can be classified. The final recognition has a high accuracy rate, and can identify unrecyclable garbage and recyclable garbage.

Key words: convolutional neural networks, group normalization, image classification, deep learning