Application of Deep Learning Based on Garbage Image Classification

In recent years, with the rapid development of economy, the country's various construction is thriving, and remarkable achievements. At the same time, resources and the environment have been seriously damaged. This phenomenon is directly related to the irrationality of garbage classification and delivery, and the contradiction between the two is becoming increasingly acute as people strongly reflect the problem of environmental pollution but do nothing about it. This paper designs a garbage image classification system based on deep learning, the main research content is to compare multiple deep learning neural network models, find the optimal classifier, develop web applications and deploy neural networks, which includes image data acquisition, image pre-processing, and comparison of VGG16, Inception, and Resnet neural network model accuracy.