Paper Abstract and Keywords |
Presentation |
2020-03-06 13:25
Detection of running area from forest road images with different image quality using deep learning Misato Ushiro, Tetsuya Higashino, Yuukou Horita (Univ. of Toyama) IMQ2019-60 IE2019-142 MVE2019-81 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Natural disasters such as falling rocks and landslides are increasing year by year on forest roads in hilly and mountainous areas. It is expected that accidents can be mitigated if it is possible to accurately detect and share information for the danger place caused by falling rocks and landslides on forest roads obtained by using images acquired from car mounted cameras. However, there is no image data set with a label for road images where landslides and road cracks that interfere with traffic due to natural disasters. In this study, we investigate a method for accurately detecting driving possible area on forest roads by actually taking forest roads and deep learning using collected image data sets. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Image processing / Forest roads / Semantic image segmentation / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 119, no. 454, IMQ2019-60, pp. 231-234, March 2020. |
Paper # |
IMQ2019-60 |
Date of Issue |
2020-02-27 (IMQ, IE, MVE) |
ISSN |
Print edition: ISSN 0913-5685 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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IMQ2019-60 IE2019-142 MVE2019-81 |
Conference Information |
Committee |
IE IMQ MVE CQ |
Conference Date |
2020-03-05 - 2020-03-06 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Kyushu Institute of Technology |
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Paper Information |
Registration To |
IMQ |
Conference Code |
2020-03-IE-IMQ-MVE-CQ |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Detection of running area from forest road images with different image quality using deep learning |
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Keyword(1) |
Image processing |
Keyword(2) |
Forest roads |
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Semantic image segmentation |
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1st Author's Name |
Misato Ushiro |
1st Author's Affiliation |
University of Toyama (Univ. of Toyama) |
2nd Author's Name |
Tetsuya Higashino |
2nd Author's Affiliation |
University of Toyama (Univ. of Toyama) |
3rd Author's Name |
Yuukou Horita |
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University of Toyama (Univ. of Toyama) |
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Speaker |
Author-1 |
Date Time |
2020-03-06 13:25:00 |
Presentation Time |
25 minutes |
Registration for |
IMQ |
Paper # |
IMQ2019-60, IE2019-142, MVE2019-81 |
Volume (vol) |
vol.119 |
Number (no) |
no.454(IMQ), no.456(IE), no.457(MVE) |
Page |
pp.231-234 |
#Pages |
4 |
Date of Issue |
2020-02-27 (IMQ, IE, MVE) |
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