Design of intelligent trash can be based on machine vision

Jianghai Liu; Yadong Jiang

doi:10.1117/12.2579291

10 November 2020 Design of intelligent trash can be based on machine vision

Jianghai Liu, Yadong Jiang

Proceedings Volume 11584, 2020 International Conference on Image, Video Processing and Artificial Intelligence; 1158413 (2020) https://doi.org/10.1117/12.2579291
Event: Third International Conference on Image, Video Processing and Artificial Intelligence, 2020, Shanghai, China

Abstract

This article designs smart trash that can be based on machine vision. Its primary function is to complete the automatic identification, classification, and bucketing operations of the typical garbage types in the community. The system uses a Raspberry Pi equipped with a convolutional neural network. It embeds a deep learning model to realize the identification of garbage and online communication to control the mechanical system to complete the class i f icat ion of was te into bucket s . In this paper, the accuracy of the AlexNet model, ZFNet model, and Inception V1 model top-1 are 62.5%, 64%, and 69.8%, respectively. The top-1 accuracy rate of the vgg model has reached 74%, and the accuracy of the model training can be improved to 94% by enhancing the vgg model.

Citation Download Citation

Jianghai Liu and Yadong Jiang "Design of intelligent trash can be based on machine vision", Proc. SPIE 11584, 2020 International Conference on Image, Video Processing and Artificial Intelligence, 1158413 (10 November 2020); https://doi.org/10.1117/12.2579291

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