VISIBILITY ESTIMATION VIA SPATIAL FREQUENCY AND DEEP LEARNING-BASED MACHINE LEARNING—AFFECTION OF FEATURE SELECTION IN SPATIAL FREQUENCY-BASED FEATURES

VISIBILITY ESTIMATION VIA SPATIAL FREQUENCY AND DEEP LEARNING-BASED MACHINE LEARNING—AFFECTION OF FEATURE SELECTION IN SPATIAL FREQUENCY-BASED FEATURES—

Published:2022 Issue:5 Volume:77 Page:I_1077-I_1084
ISSN:2185-6540
Container-title:Journal of Japan Society of Civil Engineers, Ser. D3 (Infrastructure Planning and Management)
language:en
Short-container-title:J. JSCE, Ser. D3

Author:

TAKAHASHI Sho¹,KAWATA Shotaro²,HAGIWARA Toru¹

Affiliation:

1. 北海道大学大学院工学研究院

2. 北海道大学大学院工学院

Publisher

Japan Society of Civil Engineers

Subject

General Medicine

Link

https://www.jstage.jst.go.jp/article/jscejipm/77/5/77_I_1077/_pdf

Reference12 articles.

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3. 3) Vaibhav, V., Konda, K. R., Kondapalli, C., Praveen, K. and Kondoju, B. : Real-time fog visibility range estimation for autonomous driving applications, 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC), pp. 1-6, 2020.

4. 4) 北村啓太朗，千葉有咲，落合達也，西村晋也：AI 画像判別を用いた冬期視程障害の予測に関する検討，雪氷研究大会，2019.

5. 5) Kawata, S., Takahashi, S. and Hagiwara, T. : An Estimation Method of Visibility Level on Winter Road Based on Multiple Features in CCTV Images, IEEE International Conference on Consumer Electronics – Taiwan (ICCE-Taiwan 2020), 2020.