Garbage Classification Algorithm Based on Deep Learning

This paper proposes a set of automated garbage sorting system and designs the garbage sorting algorithm based on the neural network and YOLO algorithm. To realize the detection of books, cans, plastic bottles, and glass bottles, we design a feature extraction, two detection layers and corresponding anchors and a loss function in turn, which are based on a neural network, the FPN idea and the detection output characteristics, respectively. The results show that the network model designed in this paper is light, with an accuracy rate of 86.9% and a speed of 15ms. When detecting multi-scale targets, the detection accuracy is above 86.5%, which can meet the real-time and accuracy requirements of the system.