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Author:

Han, Honggui (Han, Honggui.) | Zhen, Xiaoling (Zhen, Xiaoling.) | Zhang, Qiyu (Zhang, Qiyu.) | Li, Fangyu (Li, Fangyu.) | Du, Yongping (Du, Yongping.) | Gu, Yifan (Gu, Yifan.) | Wu, Yufeng (Wu, Yufeng.)

Indexed by:

EI Scopus

Abstract:

Rapid development of telecommunication technology in China has led to a prosperous market of smart phones, as well as an increase number of used phones. Nevertheless, there are key factors affecting the used phone recycling, one of which is the phone color. To realize an accurate automatic color recognition of used phones to enhance the recycling process, a high-dimensional spatial color conversion deep convolutional neural network (HSCCNet) is proposed in this paper. First, we established a common dataset for the field of used electronic devices. Second, the phone color is converted to the high-dimensional space of hue, saturation and value (HSV), which generates richer expressions of color features and improves the model sensitivity. Finally, a deep convolutional structure for HSV features is designed, where color feature conversion are implemented, resulting in enhanced color feature expressions. Promising results are obtained through the comparison between the proposed HSCCNet and the state-of-the-art models. © 2022

Keyword:

Recycling Smartphones Color Deep neural networks Convolution Convolutional neural networks

Author Community:

  • [ 1 ] [Han, Honggui]Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China
  • [ 2 ] [Han, Honggui]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, 100124, China
  • [ 3 ] [Han, Honggui]Engineering Research Center of Digital Community Ministry of Education, Beijing University of Technology, Beijing, 100124, China
  • [ 4 ] [Han, Honggui]Beijing Artificial Intelligence Institute and Beijing Laboratory for Intelligent Environmental Protection, Beijing, 100124, China
  • [ 5 ] [Zhen, Xiaoling]Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China
  • [ 6 ] [Zhen, Xiaoling]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, 100124, China
  • [ 7 ] [Zhang, Qiyu]Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China
  • [ 8 ] [Zhang, Qiyu]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, 100124, China
  • [ 9 ] [Li, Fangyu]Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China
  • [ 10 ] [Li, Fangyu]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, 100124, China
  • [ 11 ] [Li, Fangyu]Engineering Research Center of Digital Community Ministry of Education, Beijing University of Technology, Beijing, 100124, China
  • [ 12 ] [Li, Fangyu]Beijing Artificial Intelligence Institute and Beijing Laboratory for Intelligent Environmental Protection, Beijing, 100124, China
  • [ 13 ] [Du, Yongping]Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China
  • [ 14 ] [Du, Yongping]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, 100124, China
  • [ 15 ] [Gu, Yifan]College of Materials Science and Engineering, Beijing University of Technology, Beijing, China
  • [ 16 ] [Gu, Yifan]Institute of Circular Economy, Beijing University of Technology, Beijing, China
  • [ 17 ] [Wu, Yufeng]College of Materials Science and Engineering, Beijing University of Technology, Beijing, China
  • [ 18 ] [Wu, Yufeng]Institute of Circular Economy, Beijing University of Technology, Beijing, China

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Source :

Resources, Conservation and Recycling

ISSN: 0921-3449

Year: 2022

Volume: 187

1 3 . 2

JCR@2022

1 3 . 2 0 0

JCR@2022

ESI Discipline: ENVIRONMENT/ECOLOGY;

ESI HC Threshold:47

JCR Journal Grade:1

CAS Journal Grade:1

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 5

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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