Environment Recognition for Electric Wheelchair Based on YOLOv2-Reference-Cited by-同舟云学术

Environment Recognition for Electric Wheelchair Based on YOLOv2

Published:2018 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 3rd International Conference on Biomedical Signal and Image Processing - ICBIP '18
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Author:

Sakai Yuki¹,Lu Huimin¹,Tan Joo Kooi¹,Kim Hyoungseop¹

Affiliation:

1. Graduate School of Engineering, Kyushu Institute of Technology, Kitakyushu, Fukuoka, Japan

Publisher

ACM Press

Reference13 articles.

1. Ministry of Internal Affairs and Communications, Toukei Kara Mita Wagakunino Koreisha (The elderly in our country viewed from statistics), http://www.stat.go.jp/data/topics/pdf/topics103.pdf (2018/2/2access) (Japanese).

2. Electric wheelchair safety dissemination association, Shukka Disu No Suii (Trends in shipments), http://www.den-ankyo.org/society/transition.html (2018/1/9 access) (Japanese).

3. National Police Agency, Dendokurumaisu No Jiko (Electric wheelchair accident), https://www.npa.go.jp/koutsuu/kikaku13/shi_04jikojittai.pdf (2018/1/31 access) (Japanese).

4. Consumer Agency, Handorugata Dendokurumaisu Wo Siyoutyu No Jiko Ni Tuite No Hokokusho (Report on accidents using handwheel electric wheelchair), http://www.caa.go.jp/csic/action/pdf/9_houkoku_honbun.pdf (2018/1/9 access) (Japanese).

5. T. Pohlen et al., "Full-Resolution Residual Networks for Semantic Segmentation in Street Scenes", IEEE Conference on Computer Vision and Pattern Recognition, pp.4151--4160, 2017.

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