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Paper Abstract and Keywords
Presentation 2012-09-21 09:55
Optimization of computational complexity in Content Based Image Retrieval using Pulse Coupled Neural Network
Yuta Ishida, Hiroaki Kurokawa (Tokyo Univ of Tech) CAS2012-39 NLP2012-65
Abstract (in Japanese) (See Japanese page) 
(in English) Pulse Coupled Neural Network(PCNN) is a neural network model composed of spiking neuron.
By correspondence with the pixels of the image, the neurons are arranged in a two-dimensional lattice, studies of various image processing have been proposed.
On the other hand, share of images of large number has been made easier by the spread of internet.
In order to search for similar images using these images, there is Content Based Image Retrieval(CBIR) using image itself as search key.
CBIR is to search for images that have similar features to image features.
In order to determine the features of the image, the method using PCNN is proposed.
In CBIR using PCNN, do a search for similar image using the feature quantity called PCNN-Icon.
PCNN-Icon is time series of the number of firing neurons in PCNN, this length affects the retrieval accuracy.
This length also affects the amount of computation search.
In the case of operation as a system, it is necessary to determine the length of the PCNN-Icon to optimize the load on the system and the retrieval accuracy.
In this study, the optimization of search accuracy and seach speed.
Optimization shows the effect on the amount of computation required for search and retrival accuracy in length PCNN-Icon.
Keyword (in Japanese) (See Japanese page) 
(in English) Pulse Coupled Neural Network / Content Based Image Retrieval / / / / / /  
Reference Info. IEICE Tech. Rep., vol. 112, no. 205, NLP2012-65, pp. 49-54, Sept. 2012.
Paper # NLP2012-65 
Date of Issue 2012-09-13 (CAS, NLP) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
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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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Conference Information
Committee NLP CAS  
Conference Date 2012-09-20 - 2012-09-21 
Place (in Japanese) (See Japanese page) 
Place (in English) Eikokuji Campus, University of Kochi 
Topics (in Japanese) (See Japanese page) 
Topics (in English) General 
Paper Information
Registration To NLP 
Conference Code 2012-09-NLP-CAS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Optimization of computational complexity in Content Based Image Retrieval using Pulse Coupled Neural Network 
Sub Title (in English)  
Keyword(1) Pulse Coupled Neural Network  
Keyword(2) Content Based Image Retrieval  
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1st Author's Name Yuta Ishida  
1st Author's Affiliation Tokyo University of Technology (Tokyo Univ of Tech)
2nd Author's Name Hiroaki Kurokawa  
2nd Author's Affiliation Tokyo University of Technology (Tokyo Univ of Tech)
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Speaker
Date Time 2012-09-21 09:55:00 
Presentation Time 25 
Registration for NLP 
Paper # IEICE-CAS2012-39,IEICE-NLP2012-65 
Volume (vol) IEICE-112 
Number (no) no.204(CAS), no.205(NLP) 
Page pp.49-54 
#Pages IEICE-6 
Date of Issue IEICE-CAS-2012-09-13,IEICE-NLP-2012-09-13 


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