| Presentation | 2019-03-09 Proposition of Multimodal Time Series Data Analysis Framework by CNN based on Multi-Channel Image Conversion Komei Hiruta, Toshiki Hariki, Eichi Takaya, Kazuki Ito, Daiki Aramami, Takao Inagaki, Norio Yamagishi, Satoshi Kurihara, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In recent years, with the development of IoT and sensor technology, various data can be acquired. In this case, it is expected to establish analytical methods capable of extracting the characteristics of relevances of each variable of multimodal data. In this study, time series variables with different dimensions on the same time axis are converted to color change images as RGB which is the three primary colors of light, and Convolution Neural Network(CNN) is applied to this. Next, we propose a method to perform more effective feature extraction by converting the image using XYZ, Lab color space reflecting the color visual stimulus with RGB as the base. We compared accuracy with existing classification method and showed the effectiveness of the proposed method. Moreover, by converting time series in various color spaces. It is suggested that higher performance feature extraction can be realized than when processing each variable as independent. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | time series data / color space / CNN |
| Paper # | AI2018-54 |
| Date of Issue | 2019-03-02 (AI) |
| Conference Information | |
| Committee | AI / IPSJ-ICS / JSAI-KBS / JSAI-DOCMAS / JSAI-SAI |
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| Conference Date | 2019/3/7(4days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Tsunenori Mine(Kyushu Univ.) |
| Vice Chair | Daisuke Katagami(Tokyo Polytechnic Univ.) / Naoki Fukuta(Shizuoka Univ.) |
| Secretary | Daisuke Katagami(Ritsumeikan Univ.) / Naoki Fukuta(Univ. of Electro-Comm.) |
| Assistant | Yuko Sakurai(AIST) |
| Paper Information | |
| Registration To | Technical Committee on Artificial Intelligence and Knowledge-Based Processing / Special Interest Group on Intelligence and Complex Systems / Special Interest Group on Knowledge-Based Systems / Special Interest Group on Data Oriented Constructive Mining and Simulation / Special Interest Group on Society and Artificial Intelligence |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Proposition of Multimodal Time Series Data Analysis Framework by CNN based on Multi-Channel Image Conversion |
| Sub Title (in English) | |
| Keyword(1) | time series data |
| Keyword(2) | color space |
| Keyword(3) | CNN |
| 1st Author's Name | Komei Hiruta |
| 1st Author's Affiliation | Keio University(Keio Univ.) |
| 2nd Author's Name | Toshiki Hariki |
| 2nd Author's Affiliation | Keio University(Keio Univ.) |
| 3rd Author's Name | Eichi Takaya |
| 3rd Author's Affiliation | Keio University(Keio Univ.) |
| 4th Author's Name | Kazuki Ito |
| 4th Author's Affiliation | NetOne Systems(NetOne) |
| 5th Author's Name | Daiki Aramami |
| 5th Author's Affiliation | NetOne Systems(NetOne) |
| 6th Author's Name | Takao Inagaki |
| 6th Author's Affiliation | TOYOTA MOTOR Co.(TOYOTA) |
| 7th Author's Name | Norio Yamagishi |
| 7th Author's Affiliation | TOYOTA MOTOR Co.(TOYOTA) |
| 8th Author's Name | Satoshi Kurihara |
| 8th Author's Affiliation | Keio University(Keio Univ.) |
| Date | 2019-03-09 |
| Paper # | AI2018-54 |
| Volume (vol) | vol.118 |
| Number (no) | AI-492 |
| Page | pp.pp.7-11(AI), |
| #Pages | 5 |
| Date of Issue | 2019-03-02 (AI) |