Authors
Longyu Gao1, Fengzhi Dai1, 2, *, Zhiqing Xiao1, Jiangyu Wu1, Zilong Liu1
1Tianjin University of Science and Technology, China
2Tianjin Tianke Intelligent and Manufacture Technology Co., Ltd, China
*Corresponding author. Email: [email protected]; www.tust.edu.cn
Corresponding Author
Fengzhi Dai
Received 25 October 2020, Accepted 29 July 2021, Available Online 27 December 2021.
DOI
https://doi.org/10.2991/jrnal.k.211108.009How to use a DOI?
Keywords
Garbage classification; machine vision; deep learning; auxiliary sensors
Abstract
To improve the accuracy of front-end recognition in the garbage classification process, the recognition accuracy of the automatic garbage classification system designed based on machine vision is significantly higher than that of the traditional smart garbage can. However, the recognition accuracy rate for irregular garbage is low. To solve such problems, four types of auxiliary sensors are added to the trash can, through the mutual cooperation between the sensors, combined with the results of machine vision recognition for comprehensive judgment, greatly improving the recognition accuracy of irregular trash. It shows the broad application prospects of the research results of this paper in waste classification and environmental protection.
Copyright
© 2021 The Authors. Published by ALife Robotics Corp. Ltd.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).