| Presentation | 2022-11-30 Deep Learning-based Hierarchical Object Detection System for High-Resolution Images Yusei Horikawa, Makoto Sugaya, Renpei Yoshida, Kazuma Mashiko, Tetsuya Matsumura, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | This paper describes a new deep learning-based hierarchical object detection algorithm for high-resolution vision sensors. The proposed algorithm features hierarchical three-layers structure based on YOLO network. Wide area detection using a reduced image and local area detection using the original image are performed hierarchically for Full-HD images. These structure is anticipated to improve detecting performance as detect various size of objects. In evaluations with the VisDrone data set which is consisted by high-resolution images, our algorithm achieves about two times the number of detections and an improved mean average precision(mAP) of about 3% compared to the conventional algorithm. We also implemented this system on a small, low-cost JetsonNano board and confirmed real-time operation at approximately 3 frames per second. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Object Detection / High-Resolution Images / Deep Learning / YOLO / Embedded System |
| Paper # | VLD2022-44,ICD2022-61,DC2022-60,RECONF2022-67 |
| Date of Issue | 2022-11-21 (VLD, ICD, DC, RECONF) |
| Conference Information | |
| Committee | VLD / DC / RECONF / ICD / IPSJ-SLDM |
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| Conference Date | 2022/11/28(3days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Kanazawa Bunka Hall |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Design Gaia 2022 -New Field of VLSI Design- |
| Chair | Minako Ikeda(NTT) / Tatsuhiro Tsuchiya(Osaka Univ.) / Kentaro Sano(RIKEN) / Masafumi Takahashi(Kioxia) / Hiroyuki Ochi(Ritsumeikan Univ.) |
| Vice Chair | Shigetoshi Nakatake(Univ. of Kitakyushu) / Toshinori Hosokawa(Nihon Univ.) / Yoshiki Yamaguchi(Tsukuba Univ.) / Tomonori Izumi(Ritsumeikan Univ.) / Makoto Ikeda(Univ. of Tokyo) |
| Secretary | Shigetoshi Nakatake(NBS) / Toshinori Hosokawa(Hirosaki Univ.) / Yoshiki Yamaguchi(Nihon Univ.) / Tomonori Izumi(Chiba Univ.) / Makoto Ikeda(NEC) / (Toyohashi Univ. of Tech.) |
| Assistant | Takuma Nishimoto(Hitachi) / / Yukitaka Takemura(INTEL) / Yasunori Osana(Ryukyu Univ.) / Yoshiaki Yoshihara(KIOXIA) / Jun Shiomi(Osaka Univ.) / Takeshi Kuboki(Sony Semiconductor Solutions) |
| Paper Information | |
| Registration To | Technical Committee on VLSI Design Technologies / Technical Committee on Dependable Computing / Technical Committee on Reconfigurable Systems / Technical Committee on Integrated Circuits and Devices / Special Interest Group on System and LSI Design Methodology |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Deep Learning-based Hierarchical Object Detection System for High-Resolution Images |
| Sub Title (in English) | |
| Keyword(1) | Object Detection |
| Keyword(2) | High-Resolution Images |
| Keyword(3) | Deep Learning |
| Keyword(4) | YOLO |
| Keyword(5) | Embedded System |
| 1st Author's Name | Yusei Horikawa |
| 1st Author's Affiliation | Nihon University(Nihon Univ.) |
| 2nd Author's Name | Makoto Sugaya |
| 2nd Author's Affiliation | Nihon University(Nihon Univ.) |
| 3rd Author's Name | Renpei Yoshida |
| 3rd Author's Affiliation | Nihon University(Nihon Univ.) |
| 4th Author's Name | Kazuma Mashiko |
| 4th Author's Affiliation | Nihon University(Nihon Univ.) |
| 5th Author's Name | Tetsuya Matsumura |
| 5th Author's Affiliation | Nihon University(Nihon Univ.) |
| Date | 2022-11-30 |
| Paper # | VLD2022-44,ICD2022-61,DC2022-60,RECONF2022-67 |
| Volume (vol) | vol.122 |
| Number (no) | VLD-283,ICD-284,DC-285,RECONF-286 |
| Page | pp.pp.144-149(VLD), pp.144-149(ICD), pp.144-149(DC), pp.144-149(RECONF), |
| #Pages | 6 |
| Date of Issue | 2022-11-21 (VLD, ICD, DC, RECONF) |