{"links":{},"id":216966,"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00216966","sets":["1164:4619:10826:10881"]},"path":["10881"],"owner":"44499","recid":"216966","title":["敵対的訓練を用いたドメイン不変な特徴抽出"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-03-03"},"_buckets":{"deposit":"f846c00d-c652-448f-99cc-d44dcb949de9"},"_deposit":{"id":"216966","pid":{"type":"depid","value":"216966","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"敵対的訓練を用いたドメイン不変な特徴抽出","author_link":["561163","561161","561162"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"敵対的訓練を用いたドメイン不変な特徴抽出"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"セッション5-B ","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2022-03-03","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"千葉大学大学院融合理工学府"},{"subitem_text_value":"千葉大学大学院工学研究院"},{"subitem_text_value":"千葉大学大学院工学研究院"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"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/216966/files/IPSJ-CVIM22229035.pdf","label":"IPSJ-CVIM22229035.pdf"},"date":[{"dateType":"Available","dateValue":"2024-03-03"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CVIM22229035.pdf","filesize":[{"value":"6.7 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"20"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"7710f385-a91d-40e1-94e3-bfe8deda73b2","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2022 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"藤井, 一磨"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"計良, 宥志"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"川本, 一彦"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11131797","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8701","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"深層学習を用いた物体検出では，ソースドメインとターゲットドメインの間に背景やスタイルなどに大きな乖離があるとき，ターゲットドメインでの検出性能が低下してしまう．このドメインシフト問題は，深層モデルがソースドメインに固有な特徴を抽出するために起こる．本研究では，深層モデルに対する敵対的攻撃に対してロバストな特徴がドメイン不変な性質を持つことを利用し，教師無しドメイン適応のための特徴抽出法を提案する．提案手法では，ソースドメインでの深層物体検出モデルの敵対的訓練によりロバストな特徴を抽出しつつ，ソースドメインとターゲットドメイン間の特徴アライメントを加えることでドメイン適応を実現している．さらに，提案手法のターゲットドメインでの検出精度は，ソースドメインからの Frechet 距離が大きいほど向上することを発見し実験的に検証している．この結果を用いれば，提案手法の有効性を深層学習前に判定することができる．検証用データセットを用いた実験で，ベースラインと比較しつつ提案手法の有効性を示している．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"8","bibliographic_titles":[{"bibliographic_title":"研究報告コンピュータビジョンとイメージメディア（CVIM）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2022-03-03","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"35","bibliographicVolumeNumber":"2022-CVIM-229"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T01:17:28.601718+00:00","updated":"2025-01-19T15:40:21.183862+00:00"}