Application of visual recognition technology in machine learning-driven waste sorting

In today's society, the output of garbage is more and more, and people are indispensable for the management and classification of garbage. The recycling of garbage is also a hot topic today. The project will propose an artificial intelligence garbage classification system based on machine learning, the data set contains many photo sets, the dataset has been divided into many detailed categories, such as battery class, clothing class, cardboard class, etc. The machine learning model will learn classification through the huge data set, the model will also introduce cameras, the identified garbage is photographed and stored. The model will then call the photos that have been stored, and then identify and classify the output. Our goal is to accurately identify garbage and classify them, and people can quickly divide garbage through this model, which can be better and more targeted to take garbage for reuse, and has better help for the preparation work in the field of garbage reuse and garbage classification.