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Paper Abstract and Keywords
Presentation 2018-12-14 14:25
Training of Traffic Sign Detector and Classifier Using Synthetic Road Scenes
Akira Sekizawa, Katsuto Nakajima (TDU) PRMU2018-89
Abstract (in Japanese) (See Japanese page) 
(in English) This paper proposes a method of providing an end-to-end object recognition system based on deep learning that uses synthetically generated road scenes as recognition training images in place of actual images of road signs. Conventional training image generation methods often generate only small images that include just the traffic sign part and are not capable of training end-to-end object recognition systems using entire scenes as the training images. This paper proposes a method of synthetically generating road scenes as end-to-end object recognition system training data; the system shows that generating scenes considering contextual information around traffic signs effectively improves precision.
Keyword (in Japanese) (See Japanese page) 
(in English) Traffic Sign Recognition / Object Detection / Synthetic Data / Data Augmentation / / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 362, PRMU2018-89, pp. 73-78, Dec. 2018.
Paper # PRMU2018-89 
Date of Issue 2018-12-06 (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)
Download PDF PRMU2018-89

Conference Information
Committee PRMU  
Conference Date 2018-12-13 - 2018-12-14 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To PRMU 
Conference Code 2018-12-PRMU 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Training of Traffic Sign Detector and Classifier Using Synthetic Road Scenes 
Sub Title (in English)  
Keyword(1) Traffic Sign Recognition  
Keyword(2) Object Detection  
Keyword(3) Synthetic Data  
Keyword(4) Data Augmentation  
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1st Author's Name Akira Sekizawa  
1st Author's Affiliation Tokyo Denki University (TDU)
2nd Author's Name Katsuto Nakajima  
2nd Author's Affiliation Tokyo Denki University (TDU)
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Speaker Author-1 
Date Time 2018-12-14 14:25:00 
Presentation Time 15 minutes 
Registration for PRMU 
Paper # PRMU2018-89 
Volume (vol) vol.118 
Number (no) no.362 
Page pp.73-78 
#Pages 6 
Date of Issue 2018-12-06 (PRMU) 

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