Paper Abstract and Keywords |
Presentation |
2021-10-09 11:00
Road Damage Detection Using Global and Local Features Jinhong Yu, Yu Wang, Jien Kato (Rits Univ.) PRMU2021-22 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In this paper, we propose a road damage detection method called Global-Local Faster CNN to deal with the issue of big variation in road damage magnitude. To detect road damages of various sizes simultaneously, we combine two backbone networks under the Faster R-CNN paradigm: one with a large receptive field such as VggNet or ResNet, and another with small receptive fields such as BagNet. Experiments on RDD2020 (from the Global Road Detection Challenge) show that by fusing local features (getting from BagNet) and global features (getting from VggNet/ResNet), we can improve the detection accuracy. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
damage detection / reveptive field / CNN / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 121, no. 192, PRMU2021-22, pp. 34-39, Oct. 2021. |
Paper # |
PRMU2021-22 |
Date of Issue |
2021-10-01 (PRMU) |
ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
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PRMU2021-22 |
Conference Information |
Committee |
PRMU |
Conference Date |
2021-10-08 - 2021-10-09 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Online |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Processes and technologies to make research more efficient |
Paper Information |
Registration To |
PRMU |
Conference Code |
2021-10-PRMU |
Language |
English (Japanese title is available) |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Road Damage Detection Using Global and Local Features |
Sub Title (in English) |
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damage detection |
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reveptive field |
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CNN |
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1st Author's Name |
Jinhong Yu |
1st Author's Affiliation |
Ritsumeikan University (Rits Univ.) |
2nd Author's Name |
Yu Wang |
2nd Author's Affiliation |
Ritsumeikan University (Rits Univ.) |
3rd Author's Name |
Jien Kato |
3rd Author's Affiliation |
Ritsumeikan University (Rits Univ.) |
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Speaker |
Author-1 |
Date Time |
2021-10-09 11:00:00 |
Presentation Time |
15 minutes |
Registration for |
PRMU |
Paper # |
PRMU2021-22 |
Volume (vol) |
vol.121 |
Number (no) |
no.192 |
Page |
pp.34-39 |
#Pages |
6 |
Date of Issue |
2021-10-01 (PRMU) |
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