AGC: automated machine learning for garbage classification on mobile devices

Abstract

To protect the environment, governments introduced many policies about garbage recycling and garbage classification. However, the different garbage classification policies between different areas bring many inconveniences for people who come from other areas. In the meantime, the development of garbage classification application requires developers to have lots of experience about object classification. In this work, we employed Automated Machine Learning for the garbage classification application, which is called AGC method. The AGC method uses Google AutoML service to train the garbage classification model with Baidu AI studio garbage dataset. During train the model, we set the data augmentation and normalization to increase the precision of the model. To compare model effects, the model trained by AutoML was compared with MobileNet. At the end, the model was deployed on an iPhone to test the model. Our method achieves 0.92 in precision, which is much higher than MobileNet, and the application correctly recognized the real-word garbage image with 0.87 confidence.

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