2018年3月26日
Road-illuminance level inference across road networks based on Bayesian analysis
2018 IEEE International Conference on Consumer Electronics, ICCE 2018
- ,
- ,
- 巻
- 2018-
- 号
- 開始ページ
- 1
- 終了ページ
- 6
- 記述言語
- 英語
- 掲載種別
- 研究論文(国際会議プロシーディングス)
- DOI
- 10.1109/ICCE.2018.8326207
- 出版者・発行元
- Institute of Electrical and Electronics Engineers Inc.
This paper proposes a road-illuminance level inference method based on the naive Bayesian analysis. We investigate quantities and types of road lights and landmarks with a large set of roads in real environments and reorganize them into two safety classes, safe or unsafe, with seven road attributes. Then we carry out data learning using three types of datasets according to different groups of the road attributes. Experimental results demonstrate that the proposed method successfully classifies a set of roads with seven attributes into safe ones and unsafe ones with the accuracy of more than 85%, which is superior to other machine-learning based methods and a manual-based method.
- リンク情報
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- DOI
- https://doi.org/10.1109/ICCE.2018.8326207
- DBLP
- https://dblp.uni-trier.de/rec/conf/iccel/BaoYT18
- URL
- http://dblp.uni-trier.de/db/conf/iccel/icce2018.html#conf/iccel/BaoYT18
- Scopus
- https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85048842571&origin=inward
- Scopus Citedby
- https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85048842571&origin=inward
- ID情報
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- DOI : 10.1109/ICCE.2018.8326207
- DBLP ID : conf/iccel/BaoYT18
- SCOPUS ID : 85048842571