E3S Web Conf.
Volume 267, 20217th International Conference on Energy Science and Chemical Engineering (ICESCE 2021)
|Number of page(s)||4|
|Section||Energy Development and Utilization and Energy-Saving Technology Application|
|Published online||04 June 2021|
Research on Household Waste Detection System Based on Deep Learning
Institute of Automation, Chinese Academy of Sciences, Intelligent Manufacturing Technology and System Research Center, Beijing 100190
* Corresponding author’s e-mail: firstname.lastname@example.org
Household waste is threatening the urban environment increasingly day by day for people’s material needs increasing with the acceleration of urbanization. In this paper, a new waste sorting model is proposed to solve the problems of waste sorting. The style transfer was used to increase the data set to make some objects be sorted well. Then the rotational attention mechanism model was used to increase the accuracy of waste sorting of the blocked objects. The representation vector extraction module in the target tracking algorithm Deep Sort was replaced with Siamese network to make the network more lightweight. As a result, this paper effectively solves the current waste sorting tasks.
© The Authors, published by EDP Sciences, 2021
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