Presentation | 2017-06-23 Visibility Prediction of Color Scheme with the Model of Human Color Vision composed of Convolutional Neural Networks Shodai Sasaki, Yoshihisa Shinozawa, |
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PDF Download Page | PDF download Page Link |
Abstract(in Japanese) | (See Japanese page) |
Abstract(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 researchon the evaluation of visibility prediction. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Multi-Stage Color Model / color scheme / visibility prediction / convolutional neural networks |
Paper # | NC2017-11 |
Date of Issue | 2017-06-16 (NC) |
Conference Information | |
Committee | NC / IPSJ-BIO / IBISML / IPSJ-MPS |
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Conference Date | 2017/6/23(3days) |
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 |
Chair | Masafumi Hagiwara(Keio Univ.) / / Kenji Fukumizu(ISM) |
Vice Chair | Yutaka Hirata(Chubu Univ.) / / Masashi Sugiyama(Univ. of Tokyo) |
Secretary | Yutaka Hirata(Tokyo Inst. of Tech.) / (Nagoya Univ.) / Masashi Sugiyama / (Kyoto Univ.) |
Assistant | Yoshihisa Shinozawa(Keio Univ.) / Keiichiro Inagaki(Chubu Univ.) / / Ichiro Takeuchi(Nagoya Inst. of Tech.) / Toshihiro Kamishima(AIST) |
Paper Information | |
Registration To | Technical Committee on Neurocomputing / Special Interest Group on Bioinformatics and Genomics / Technical Committee on Infomation-Based Induction Sciences and Machine Learning / Special Interest Group on Mathematical Modeling and Problem Solving |
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Language | JPN |
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) | |
Keyword(1) | Multi-Stage Color Model |
Keyword(2) | color scheme |
Keyword(3) | visibility prediction |
Keyword(4) | convolutional neural networks |
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.) |
Date | 2017-06-23 |
Paper # | NC2017-11 |
Volume (vol) | vol.117 |
Number (no) | NC-109 |
Page | pp.pp.39-44(NC), |
#Pages | 6 |
Date of Issue | 2017-06-16 (NC) |