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深層学習を用いたコンクリート構造物のひび割れ抽出・判別方法に関する研究
http://hdl.handle.net/10069/40251
http://hdl.handle.net/10069/402511a463f9b-1d10-4d49-be1b-44c3e817539e
名前 / ファイル | ライセンス | アクション |
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50_95_71.pdf (1.1 MB)
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Item type | 紀要論文 / Departmental Bulletin Paper(1) | |||||
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公開日 | 2020-09-09 | |||||
タイトル | ||||||
タイトル | 深層学習を用いたコンクリート構造物のひび割れ抽出・判別方法に関する研究 | |||||
言語 | ||||||
言語 | jpn | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | analysis | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | inspection | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | administering | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | maintenance | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | deep learning | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | cracking concrete | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | automatic | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | assessment | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | extraction | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
資源タイプ | departmental bulletin paper | |||||
著者 |
寺野, 聡恭
× 寺野, 聡恭× 出水, 享× 古賀, 掲維× 中島, 賢哉× 松田, 浩 |
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著者別名 | ||||||
姓名 | TERANO, Sousuke | |||||
著者別名 | ||||||
姓名 | DEMIZU, Akira | |||||
著者別名 | ||||||
姓名 | KOGA, Aoi | |||||
著者別名 | ||||||
姓名 | NAKASHIMA, Kenya | |||||
著者別名 | ||||||
姓名 | MATSUDA, Hiroshi | |||||
その他のタイトル | ||||||
その他のタイトル | A Study on Crack Extraction and Discrimination Method of Concrete Structures Using Deep Learning | |||||
抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | In visual inspection of concrete structures, it is basically necessary to observe the occurrence of cracks. The current inspection method for concrete structures is that the inspector creates a sketch by visual inspection.However, this method has many problems such as requiring enormous amount of work time and amount of work and depending on the knowledge and experience of the inspector. The purpose of this study is to automatically extract cracks (including crack width) on concrete surface from digital images using image analysis techniques such as deep learning and transfer learning. | |||||
書誌情報 |
長崎大学大学院工学研究科研究報告 en : Reports of Graduate School of Engineering, Nagasaki University 巻 50, 号 95, p. 71-76, 発行日 2020-07 |
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ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 18805574 | |||||
著者版フラグ | ||||||
出版タイプ | VoR | |||||
出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||
出版者 | ||||||
出版者 | 長崎大学大学院工学研究科 | |||||
出版者別言語 | ||||||
Graduate School of Engineering, Nagasaki University | ||||||
sortkey | ||||||
12 | ||||||
引用 | ||||||
内容記述タイプ | Other | |||||
内容記述 | 長崎大学大学院工学研究科研究報告, 50(95), pp.71-76; 2020 |