{"created":"2024-03-27T01:18:44.497213+00:00","id":2000043,"links":{},"metadata":{"_buckets":{"deposit":"739afe4a-ddfe-4bc9-8090-936d6a7ee60b"},"_deposit":{"created_by":15,"id":"2000043","owner":"15","owners":[15],"pid":{"revision_id":0,"type":"depid","value":"2000043"},"status":"published"},"_oai":{"id":"oai:cis.repo.nii.ac.jp:02000043","sets":["3:1709184245895"]},"author_link":[],"control_number":"2000043","item_10002_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2024-03-28","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"17","bibliographicPageEnd":"65","bibliographicPageStart":"58","bibliographic_titles":[{"bibliographic_title":"千葉科学大学紀要","bibliographic_titleLang":"ja"},{"bibliographic_title":"The University Bulletin of Chiba Insitute of Science","bibliographic_titleLang":"en"}]}]},"item_10002_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"近年，大規模な水害による道路の浸水被害が多発しており，道路の被害状況を早期に把握できれば復旧活動の迅速化において有意であると考えられる．これまで行なわれてきた衛星画像や空中写真からの浸水道路の判別は熟練者が行なっており，これらの作業の自動化が期待されている．自動化については，従来のコンピュータを用いた解析手法もあるが，近年，AIによる手法が試みられている．本研究は，災害発生後の空中写真から道路の浸水被害箇所を迅速かつ自動的に特定することを目的とし，AI技術の導入を試みた．ResNet34を使用してセマンティックセグメンテーションを行い，画像中の浸水道路を判別した．その結果，浸水道路と併せて浸水していない道路も同時に学習させることによって，浸水道路の判別精度が向上することが明らかとなった．\n\nKeywords: 深層学習，ResNet，Segmentation，空中写真","subitem_description_language":"ja","subitem_description_type":"Abstract"}]},"item_10002_full_name_3":{"attribute_name":"著者（英）","attribute_value_mlt":[{"names":[{"name":"YAMAGUCHI, Yuki","nameLang":"en"},{"name":"FUJIMOTO, Ryuto","nameLang":"en"},{"name":"TODA, Kazuyuki","nameLang":"en"}]}]},"item_10002_publisher_8":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"千葉科学大学","subitem_publisher_language":"ja"}]},"item_10002_source_id_11":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA1230240X","subitem_source_identifier_type":"NCID"}]},"item_10002_source_id_9":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2436-2565","subitem_source_identifier_type":"EISSN"}]},"item_10002_version_type_20":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_ab4af688f83e57aa","subitem_version_type":"AM"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"山口,　裕基","creatorNameLang":"ja"}]},{"creatorNames":[{"creatorName":"藤本,　龍虎","creatorNameLang":"ja"}]},{"creatorNames":[{"creatorName":"戸田,　和之","creatorNameLang":"ja"}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2024-03-28"}],"filename":"58-65山口裕基（原著).pdf","filesize":[{"value":"715 KB"}],"format":"application/pdf","license_note":"copyright (c) 2023 by Chiba Institute of Science","licensetype":"license_note","mimetype":"application/pdf","url":{"url":"https://cis.repo.nii.ac.jp/record/2000043/files/58-65山口裕基（原著).pdf"},"version_id":"6dc11706-02a2-4b88-b709-130dfcbfbc9b"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"departmental bulletin paper","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"機械学習を用いた空中写真からの道路浸水被害箇所の特定","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"機械学習を用いた空中写真からの道路浸水被害箇所の特定","subitem_title_language":"ja"},{"subitem_title":"Identification of flooded roads from aerial photographs using machine learning techniques","subitem_title_language":"en"}]},"item_type_id":"10002","owner":"15","path":["1709184245895"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-03-28"},"publish_date":"2024-03-28","publish_status":"0","recid":"2000043","relation_version_is_last":true,"title":["機械学習を用いた空中写真からの道路浸水被害箇所の特定"],"weko_creator_id":"15","weko_shared_id":-1},"updated":"2024-05-09T07:53:11.487638+00:00"}