INVESTIGATION OF RELATIONSHIP BETWEEN WAVE CONDITIONS AND COASTAL IMAGES USING DEEP LEARNING

• MIYASHITA Yurika

  岐阜工業高等専門学校 先端融合開発専攻

• KIKU Masami

  岐阜工業高等専門学校 環境都市工学科

• NAKAMURA Tomoaki

  名古屋大学 大学院工学研究科土木工学専攻

• MIZUTANI Norimi

  名古屋大学 大学院工学研究科土木工学専攻

Bibliographic Information

Other Title

• ディープラーニングを用いた海岸画像と波浪条件の関連性の検討
• ディープラーニング オ モチイタ カイガン ガゾウ ト ハロウ ジョウケン ノ カンレンセイ ノ ケントウ

Abstract

 In assessing wave conditions influencing on topographic change, it is useful to estimate beach topography and wave conditions from coastal images. The purpose of this study is to investigate the relationship between wave conditions and coastal images taken with a network camera installed at Shichiri-Mihama Ida beach using deep learning. The coastal images were labeled with significant wave heights and periods at Owase, tidal levels at Kumano, and various values obtained from these parameters. As a result, it was revealed that the wave run-up showed high relevance to the coastal images.

Journal

• Journal of Japan Society of Civil Engineers, Ser. B3 (Ocean Engineering)

  Journal of Japan Society of Civil Engineers, Ser. B3 (Ocean Engineering) 75 (2), I_677-I_682, 2019

  Japan Society of Civil Engineers

Keywords

• convolutional neural network
• coastal erosion
• image analysis
• classification
• run-up height

Details

• CRID: 1390282752343362688
• NII Article ID: 130007725028
• NII Article ID: 40022474862
• DOI: 10.2208/jscejoe.75.i_677
• ISSN: 21854688
• NDL BIB ID: 031268193
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I031268193
• Web Site: https://www.jstage.jst.go.jp/article/jscejoe/75/2/75_I_677/_pdf
• Text Lang: ja
• Data Source:
  • JaLC
  • NDL
  • Crossref
  • CiNii Articles
  • KAKEN
• Abstract License Flag: Disallowed