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Paper Abstract and Keywords
Presentation 2019-03-06 16:40
Study on data augmentation using Fourier transform for texture image classification
Daigo Nitta, Hayaru Shouno (UEC) NC2018-87
Abstract (in Japanese) (See Japanese page) 
(in English) In the field of medical imaging such like computed tomography analysis, it is difficult to prepare a sufficient amount of labeled data for learning, and there exists bias in the number of classes.
Applying such data into a learning machine, we may obtain .

In order to overcome this problem, we propose a new data augmentation framework for case image data set of diffuse lung disease.
Specifically, we propose a method of decomposing learning data images in Fourier space and combining amplitude characteristics and phase characteristics among other classes for data augmentation.

As a result of the learning of the lesion identification problem in Deep Convolutional Neural Network using this method, the accuracy was improved compared with the conventional method such as normal linear transformation and the method proposed in recent years.
Keyword (in Japanese) (See Japanese page) 
(in English) Deep Learning / Data Augmentation / Lesion Identification / Medical image / Texture image / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 470, NC2018-87, pp. 233-238, March 2019.
Paper # NC2018-87 
Date of Issue 2019-02-25 (NC) 
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 NC2018-87

Conference Information
Committee NC MBE  
Conference Date 2019-03-04 - 2019-03-06 
Place (in Japanese) (See Japanese page) 
Place (in English) University of Electro Communications 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To NC 
Conference Code 2019-03-NC-MBE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Study on data augmentation using Fourier transform for texture image classification 
Sub Title (in English)  
Keyword(1) Deep Learning  
Keyword(2) Data Augmentation  
Keyword(3) Lesion Identification  
Keyword(4) Medical image  
Keyword(5) Texture image  
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1st Author's Name Daigo Nitta  
1st Author's Affiliation The University of Electro-Communications (UEC)
2nd Author's Name Hayaru Shouno  
2nd Author's Affiliation The University of Electro-Communications (UEC)
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Speaker
Date Time 2019-03-06 16:40:00 
Presentation Time 25 
Registration for NC 
Paper # IEICE-NC2018-87 
Volume (vol) IEICE-118 
Number (no) no.470 
Page pp.233-238 
#Pages IEICE-6 
Date of Issue IEICE-NC-2019-02-25 


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