| Presentation | 2018-05-15 Study of Automatic Landslide Disaster Danger Level Determination Method by Image Processing on Deep Learning Yusuke Ota, Koichi Shin, Masahiro Nishi, |
|---|---|
| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In order to reduce damages caused by landslide disasters, it is important to create an environment in which residents judge the timing to evacuate. Our research group operates a landslide disaster monitoring system based on the solar power supply. This system aims to promote early evacuation of residents, and it is constructed in the dangerous place where the landslide disaster occurred in the past. In this system, monitoring is carried out for 24 hours with an infrared camera. The images are uploaded on the Web page, and the residents can browse from each device. By checking the current status of each monitoring point from the Web page, residents can use the image as one of the basis of judgment of evacuation. However, in the current system, it is inefficient that residents have to visually monitor Web page in order to immediately detect the danger. Therefore, it is necessary to automatically detect that a dangerous situation has occurred, and make improvements so that notification can be sent to the residents. This study developed and evaluated images classification method by danger level by machine learning. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Landslide Disasters / Machine Learning / Deep Learning / Image Classification |
| Paper # | ICTSSL2018-13,ASN2018-13 |
| Date of Issue | 2018-05-07 (ICTSSL, ASN) |
| Conference Information | |
| Committee | ASN / ICTSSL |
|---|---|
| Conference Date | 2018/5/14(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Hiroshima City Univ. |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Ambient intelligence, safe and secure life, poster session, etc. |
| Chair | Hiraku Okada(Nagoya Univ.) / Kazunori Okada(NICT) |
| Vice Chair | Shigeki Shiokawa(KAIT) / Jin Nakazawa(Keio Univ.) / Satoru Yamano(NEC) / Hiroshi Tamura(Chuo Univ.) / Keisuke Nakano(Niigata Univ.) |
| Secretary | Shigeki Shiokawa(NICT) / Jin Nakazawa(Sophia Univ.) / Satoru Yamano(NTT DoCoMo) / Hiroshi Tamura(Shizuoka Univ.) / Keisuke Nakano |
| Assistant | Hiroto Aida(Doshisha Univ.) / Tomoyuki Ota(Hiroshima City Univ.) / Tatsuya Kikuzuki(Fujitu Lab.) / Ryo Nakano(HITACHI) / Yoshifumi Hotta(Mitsubishi Electric) / Shosuke Sato(Tohoku Univ.) / Tomotaka Wada(Kansai Univ.) / Kazuyuki Miyakita(Niigata Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Ambient intelligence and Sensor Networks / Technical Committee on Information and Communication Technologies for Safe and Secure Life |
|---|---|
| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Study of Automatic Landslide Disaster Danger Level Determination Method by Image Processing on Deep Learning |
| Sub Title (in English) | |
| Keyword(1) | Landslide Disasters |
| Keyword(2) | Machine Learning |
| Keyword(3) | Deep Learning |
| Keyword(4) | Image Classification |
| 1st Author's Name | Yusuke Ota |
| 1st Author's Affiliation | Hiroshima City University(Hiroshima City Univ.) |
| 2nd Author's Name | Koichi Shin |
| 2nd Author's Affiliation | Hiroshima City University(Hiroshima City Univ.) |
| 3rd Author's Name | Masahiro Nishi |
| 3rd Author's Affiliation | Hiroshima City University(Hiroshima City Univ.) |
| Date | 2018-05-15 |
| Paper # | ICTSSL2018-13,ASN2018-13 |
| Volume (vol) | vol.118 |
| Number (no) | ICTSSL-26,ASN-27 |
| Page | pp.pp.71-76(ICTSSL), pp.71-76(ASN), |
| #Pages | 6 |
| Date of Issue | 2018-05-07 (ICTSSL, ASN) |