Garbage classification method based on deep learning

Waste classification is an important link to realize waste reduction, harmlessness and recycling. Traditional waste classification is mostly carried out by manual sorting, which has the disadvantages of low sorting efficiency and high labor cost. With the continuous improvement of the level of intelligent equipment in China, it is possible to use computer vision intelligent equipment for waste sorting. However, traditional image classification algorithms use manual feature extraction and classification. When the type and quantity of garbage increase, the classification accuracy and efficiency of intelligent equipment will decline. The successful application of deep learning technology in the field of computer vision improves the accuracy and efficiency of image classification, which makes it a trend for deep learning technology to replace the traditional image classification algorithm for garbage classification. Therefore, it is of great significance to use deep learning technology for automatic classification of waste.