Multi-label Garbage Image Classification Based on Deep Learning

Abstract

In recent years, with the development of deep learning technology, the accuracy of image recognition has been significantly improved. Deep learning has been widely used in the recognition of single-label images. This project aims to intelligently classify domestic garbage images as application scenarios based on depth. Learn to carry out multi-label classification research on images containing multiple visual objects, and design and build a multi-label garbage image classification model to improve recognition accuracy and speed as the main research goal to conduct classification research on multi-label garbage images.