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Paper Abstract and Keywords
Presentation 2021-05-21 10:00
Scene Recognition of Omni-Directional Images by Patch-Based CNN
Takumi Hatogai, Takao Yamanaka (Sophia Univ.) PRMU2021-3
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, a scene recognition method for omni-directional images is proposed using patch-based convolutional neural networks, by extracting patches from an omni-directional image for correcting distortions in the equirectangular projection. Although the scene label of the original omni-directional image was assigned to all the patches extracted from the omni-directional image, some patches may not include the scene information at all due to the limited angle of view. These patches are not effective to the scene recognition with the patch-based convolutional neural networks. Therefore, effective patches to the scene recognition were selected based on the EM (Expectation-Maximization) algorithm, and were used for the patch-based scene recognition. As a result, the scene recognition performance was improved with the proposed method.
Keyword (in Japanese) (See Japanese page) 
(in English) Convolutional Neural Network / EM Algorithm / Omni-Directional Image / Deep Learning / / / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 23, PRMU2021-3, pp. 13-18, May 2021.
Paper # PRMU2021-3 
Date of Issue 2021-05-13 (PRMU) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
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 PRMU2021-3

Conference Information
Conference Date 2021-05-20 - 2021-05-21 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Vision & Language 
Paper Information
Registration To PRMU 
Conference Code 2021-05-PRMU-CVIM-NL 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Scene Recognition of Omni-Directional Images by Patch-Based CNN 
Sub Title (in English)  
Keyword(1) Convolutional Neural Network  
Keyword(2) EM Algorithm  
Keyword(3) Omni-Directional Image  
Keyword(4) Deep Learning  
1st Author's Name Takumi Hatogai  
1st Author's Affiliation Sophia University (Sophia Univ.)
2nd Author's Name Takao Yamanaka  
2nd Author's Affiliation Sophia University (Sophia Univ.)
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Date Time 2021-05-21 10:00:00 
Presentation Time 15 
Registration for PRMU 
Paper # IEICE-PRMU2021-3 
Volume (vol) IEICE-121 
Number (no) no.23 
Page pp.13-18 
#Pages IEICE-6 
Date of Issue IEICE-PRMU-2021-05-13 

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