| Presentation | 2020-03-05 Improvement of Road Damage Detection Method Based on Deep Learning Naoki Wada, Masaru Takeuchi, Kenji Kanai, Jiro Katto, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Recently, automatic road damage detection is required because many Japanese roads need to be repaired due to infrastructure aging problem. As related study, Road Damage Detector is proposed, and this approach adopts deep learning methods, such as SSD-Inception and SSD-MobileNet, in order to detect road damages from images captured by smartphones. However, we confirm that this method indicates low recall values through evaluation. To provide more reliable road damage detection, we study a method that combines YOLO and MobileNet. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Deep Learning / Road Damage Detecion / Image Processing |
| Paper # | IMQ2019-14,IE2019-96,MVE2019-35 |
| Date of Issue | 2020-02-27 (IMQ, IE, MVE) |
| Conference Information | |
| Committee | IE / IMQ / MVE / CQ |
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| Conference Date | 2020/3/5(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Kyushu Institute of Technology |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Hideaki Kimata(NTT) / Toshiya Nakaguchi(Chiba Univ.) / Kenji Mase(Nagoya Univ.) / Hideyuki Shimonishi(NEC) |
| Vice Chair | Kazuya Kodama(NII) / Keita Takahashi(Nagoya Univ.) / Mitsuru Maeda(Canon) / Kenya Uomori(Osaka Univ.) / Masayuki Ihara(NTT) / Jun Okamoto(NTT) / Takefumi Hiraguri(Nippon Inst. of Tech.) |
| Secretary | Kazuya Kodama(NTT) / Keita Takahashi(NHK) / Mitsuru Maeda(Shizuoka Univ.) / Kenya Uomori(Sony Semiconductor Solutions) / Masayuki Ihara(Nagoya Univ.) / Jun Okamoto(NTT) / Takefumi Hiraguri(Nippon Inst. of Tech.) |
| Assistant | Kyohei Unno(KDDI Research) / Norishige Fukushima(Nagoya Inst. of Tech.) / Hiroaki Kudo(Nagoya Univ.) / Masaru Tsuchida(NTT) / Keita Hirai(Chiba Univ.) / Satoshi Nishiguchi(Oosaka Inst. of Tech.) / Masanori Yokoyama(NTT) / Shogo Fukushima(Univ. of ToKyo) / Chikara Sasaki(KDDI Research) / Yoshiaki Nishikawa(NEC) / Takuto Kimura(NTT) |
| Paper Information | |
| Registration To | Technical Committee on Image Engineering / Technical Committee on Image Media Quality / Technical Committee on Media Experience and Virtual Environment / Technical Committee on Communication Quality |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Improvement of Road Damage Detection Method Based on Deep Learning |
| Sub Title (in English) | |
| Keyword(1) | Deep Learning |
| Keyword(2) | Road Damage Detecion |
| Keyword(3) | Image Processing |
| 1st Author's Name | Naoki Wada |
| 1st Author's Affiliation | Waseda University(Waseda Univ.) |
| 2nd Author's Name | Masaru Takeuchi |
| 2nd Author's Affiliation | Waseda University(Waseda Univ.) |
| 3rd Author's Name | Kenji Kanai |
| 3rd Author's Affiliation | Waseda University(Waseda Univ.) |
| 4th Author's Name | Jiro Katto |
| 4th Author's Affiliation | Waseda University(Waseda Univ.) |
| Date | 2020-03-05 |
| Paper # | IMQ2019-14,IE2019-96,MVE2019-35 |
| Volume (vol) | vol.119 |
| Number (no) | IMQ-454,IE-456,MVE-457 |
| Page | pp.pp.3-8(IMQ), pp.3-8(IE), pp.3-8(MVE), |
| #Pages | 6 |
| Date of Issue | 2020-02-27 (IMQ, IE, MVE) |