Paper Abstract and Keywords |
Presentation |
2017-06-23 17:15
Visibility Prediction of Color Scheme with the Model of Human Color Vision composed of Convolutional Neural Networks Shodai Sasaki, Yoshihisa Shinozawa (Keio Univ.) NC2017-11 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In this research, we implement convolutional neural networks (CNN) and introduce a multi-stage color (MSC) model, which is a human color vision model, reproduce the appearance of human color on a computer and compare the image visibility of an unknown color scheme to perform prediction. By making the reaction values of multiple cell layers of the MSC model as input for the CNN, and learning the filters, it is possible to extract the features of two or more complicated colors. In addition, in order to extract the characteristics between images in the construction of the CNN,
we propose a CNN that improves the structure. CNN learning was performed using the data of the pairwise comparison experiment. The results show that the accuracy of this method is higher than that of previous research
on the evaluation of visibility prediction. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Multi-Stage Color Model / color scheme / visibility prediction / convolutional neural networks / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 117, no. 109, NC2017-11, pp. 39-44, June 2017. |
Paper # |
NC2017-11 |
Date of Issue |
2017-06-16 (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 |
NC2017-11 |
Conference Information |
Committee |
NC IPSJ-BIO IBISML IPSJ-MPS |
Conference Date |
2017-06-23 - 2017-06-25 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Okinawa Institute of Science and Technology |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Machine Learning Approach to Biodata Mining, and General |
Paper Information |
Registration To |
NC |
Conference Code |
2017-06-NC-BIO-IBISML-MPS |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Visibility Prediction of Color Scheme with the Model of Human Color Vision composed of Convolutional Neural Networks |
Sub Title (in English) |
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Keyword(1) |
Multi-Stage Color Model |
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color scheme |
Keyword(3) |
visibility prediction |
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convolutional neural networks |
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1st Author's Name |
Shodai Sasaki |
1st Author's Affiliation |
Keio University (Keio Univ.) |
2nd Author's Name |
Yoshihisa Shinozawa |
2nd Author's Affiliation |
Keio University (Keio Univ.) |
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Speaker |
Author-2 |
Date Time |
2017-06-23 17:15:00 |
Presentation Time |
25 minutes |
Registration for |
NC |
Paper # |
NC2017-11 |
Volume (vol) |
vol.117 |
Number (no) |
no.109 |
Page |
pp.39-44 |
#Pages |
6 |
Date of Issue |
2017-06-16 (NC) |
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