{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00212716","sets":["6164:6165:6522:10650"]},"path":["10650"],"owner":"44499","recid":"212716","title":["Grad-CAMを利用した画像認識AIに対する注目箇所特定手法の提案と評価"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-08-30"},"_buckets":{"deposit":"83608d01-a1cf-4e25-8b77-053101929549"},"_deposit":{"id":"212716","pid":{"type":"depid","value":"212716","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"Grad-CAMを利用した画像認識AIに対する注目箇所特定手法の提案と評価","author_link":["543131","543130","543132","543129"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Grad-CAMを利用した画像認識AIに対する注目箇所特定手法の提案と評価"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"ポスター","subitem_subject_scheme":"Other"}]},"item_type_id":"18","publish_date":"2021-08-30","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_18_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"大阪工業大学"},{"subitem_text_value":"大阪工業大学"},{"subitem_text_value":"大阪工業大学"},{"subitem_text_value":"関西電力株式会社"}]},"item_18_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Osaka institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Osaka institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Osaka institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"The Kansai Electric Power Company, Incorporated","subitem_text_language":"en"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/212716/files/IPSJ-SES2021043.pdf","label":"IPSJ-SES2021043.pdf"},"date":[{"dateType":"Available","dateValue":"2023-08-30"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-SES2021043.pdf","filesize":[{"value":"959.0 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"12"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"ad69b8c4-e589-4c68-ace8-ab768c040b82","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2021 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"景井, 玲良"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"本田, 澄"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"細谷, 健司"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"山下, 育男"}],"nameIdentifiers":[{}]}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_5794","resourcetype":"conference paper"}]},"item_18_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"AI が出力した結果についてなぜその結果になったのか不明確であることが指摘されている．本研究は画像認識 AI に対して，対象画像の特徴量を抽出し可視化する Grad-CAM を用いて，AI がどの部分で識別したかを分析する．対象は金属組織画像 1000 枚と人為的に生成された傷のある金属組織画像 150 枚で，傷の箇所の位置と大きさは分かっている．評価方法は傷の位置と大きさと Grad-CAM の数値を用いて，数値が傷の範囲に収まっているかを見る．これにより AI が注目している箇所が，人が注目している箇所と同じかどうかを確認できる．この手法によって AI による画像分類の精度評価の助けとなると考えられる．","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"286","bibliographic_titles":[{"bibliographic_title":"ソフトウェアエンジニアリングシンポジウム2021論文集"}],"bibliographicPageStart":"285","bibliographicIssueDates":{"bibliographicIssueDate":"2021-08-30","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"2021"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":212716,"updated":"2025-01-19T17:24:17.270548+00:00","links":{},"created":"2025-01-19T01:13:38.920236+00:00"}