{"links":{},"id":232711,"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00232711","sets":["1164:4619:11539:11552"]},"path":["11552"],"owner":"44499","recid":"232711","title":["最重症度ラベルを用いたマルチインスタンス学習"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-02-25"},"_buckets":{"deposit":"45f1508f-1c00-4eb7-ba32-a38f48609817"},"_deposit":{"id":"232711","pid":{"type":"depid","value":"232711","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"最重症度ラベルを用いたマルチインスタンス学習","author_link":["630620","630621","630619","630622"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"最重症度ラベルを用いたマルチインスタンス学習"}]},"item_type_id":"4","publish_date":"2024-02-25","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"九州大学大学院システム情報科学府"},{"subitem_text_value":"九州大学大学院システム情報科学府"},{"subitem_text_value":"横浜市立大学データサイエンス学部"},{"subitem_text_value":"九州大学大学院システム情報科学府"}]},"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/232711/files/IPSJ-CVIM24237020.pdf","label":"IPSJ-CVIM24237020.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CVIM24237020.pdf","filesize":[{"value":"1.3 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"20"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"af30257c-1894-4abe-9e45-3a1e569eb184","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Institute of Electronics, Information and Communication Engineers This SIG report is only available to those in membership of the SIG."}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"志久, 開人"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"西村, 和也"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"末廣, 大貴"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"備瀬, 竜馬"}],"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":"潰瘍性大腸炎の用いる内視鏡画像に対する画像単位のアノテーションはとてもコストが高いため，患者 1 人に対して撮影される複数の画像の集合に対して，最も重症度の高い画像の診断結果のみが患者に対して記録されることがある．本研究では，複数の内視鏡画像に対し 1 つの診断ラベルが付与されている状況を，マルチインスタンス学習 (MIL) と順序回帰問題の複合問題として捉える．提案手法では，近年 MIL において有効性を示している Transformer に，一般的に順序回帰問題で用いられる K-rank algorithm を導入することで，順序関係を考慮した分類学習を行う．その際，マルチクラストークンを用いることで，各ランク分類ごとに重要となるインスタンス特徴を適応的に選択し集約を行う．公開潰瘍性大腸炎データセットを用いた実験の結果から，提案手法の有効性を確認した．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"5","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":"2024-02-25","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"20","bibliographicVolumeNumber":"2024-CVIM-237"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T01:33:44.028459+00:00","updated":"2025-01-19T10:20:45.420291+00:00"}