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Paper Abstract and Keywords
Presentation 2019-03-18 15:00
Reali-time Object Detection based on SSD
Yuya Yamashige, Masaki Aono (TUT) BioX2018-60 PRMU2018-164
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, attention has been paid to developing object detection methods from images, based on deep learning. In particular, toward self-driving cars, it is essential to make the detection as accurately as possible, as quickly as possible, as economically as possible. Here, we focus on SSD: Single Shot MultiBox Detector (SSD300) and attempt to improve it with less GPU memory. We propose a new method called “FPSSD7” (Feature Pyramid SSD7), which has less convolutional layers, keeping semantic information. For this purpose, we develop a method to interpolate semantic information between lower layers with high resolution feature maps and upper layer with low resolution features maps. We conducted comparative experiments with the conventional methods using Udacity Annotated Driving Dataset. As the result, we demonstrate that our proposed method outperform the conventional methods.
Keyword (in Japanese) (See Japanese page) 
(in English) Object Detection / Deep Learning / SSD: Single Shot MultiBox Detector / / / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 513, PRMU2018-164, pp. 181-186, March 2019.
Paper # PRMU2018-164 
Date of Issue 2019-03-10 (BioX, PRMU) 
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)
Download PDF BioX2018-60 PRMU2018-164

Conference Information
Committee PRMU BioX  
Conference Date 2019-03-17 - 2019-03-18 
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 2019-03-PRMU-BioX 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Reali-time Object Detection based on SSD 
Sub Title (in English)  
Keyword(1) Object Detection  
Keyword(2) Deep Learning  
Keyword(3) SSD: Single Shot MultiBox Detector  
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1st Author's Name Yuya Yamashige  
1st Author's Affiliation Toyohashi University of Technology (TUT)
2nd Author's Name Masaki Aono  
2nd Author's Affiliation Toyohashi University of Technology (TUT)
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Speaker Author-1 
Date Time 2019-03-18 15:00:00 
Presentation Time 15 minutes 
Registration for PRMU 
Paper # BioX2018-60, PRMU2018-164 
Volume (vol) vol.118 
Number (no) no.512(BioX), no.513(PRMU) 
Page pp.181-186 
#Pages 6 
Date of Issue 2019-03-10 (BioX, PRMU) 

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