Paper Abstract and Keywords |
Presentation |
2022-10-30 16:00
A Trial of Recognition of Electronic Parts by Deep-Learning for Efficient Recycling Yihong Tang, Tomonori Izumi (Ritsumeikan Univ.) |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In order to improve material-recycling of disposed electronic appliances, we aim to develop a system to analyze and categorize electronic boards and parts utilizing cameras over conveyor belt. We adopt deep learning technology to recognize part images. Since popular CNN models for general object recognition are over performing, we reduce and optimize the structure of the network to fit electronic parts. Our model classify a single part image within about 120[usec] with an accuracy of about 95[%]. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
electronic wastes / recycling / deep learning / CNN / resource paradox / SDGs / / |
Reference Info. |
ITE Tech. Rep., vol. 46, pp. 19-22, Oct. 2022. |
Paper # |
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Date of Issue |
2022-10-23 (AIT) |
ISSN |
Print edition: ISSN 1342-6893 Online edition: ISSN 2424-1970 |
Download PDF |
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Conference Information |
Committee |
IIEEJ AIT |
Conference Date |
2022-10-30 - 2022-10-31 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
on line |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
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Paper Information |
Registration To |
IIEEJ |
Conference Code |
2022-10-IIEEJ-AIT |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
A Trial of Recognition of Electronic Parts by Deep-Learning for Efficient Recycling |
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electronic wastes |
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recycling |
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deep learning |
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CNN |
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resource paradox |
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SDGs |
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1st Author's Name |
Yihong Tang |
1st Author's Affiliation |
Ritsumeikan University (Ritsumeikan Univ.) |
2nd Author's Name |
Tomonori Izumi |
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Ritsumeikan University (Ritsumeikan Univ.) |
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Speaker |
Author-2 |
Date Time |
2022-10-30 16:00:00 |
Presentation Time |
20 minutes |
Registration for |
IIEEJ |
Paper # |
AIT2022-177 |
Volume (vol) |
vol.46 |
Number (no) |
no.34 |
Page |
pp.19-22 |
#Pages |
4 |
Date of Issue |
2022-10-23 (AIT) |