{"created":"2025-01-19T01:33:47.490075+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00232748","sets":["1164:4619:11539:11552"]},"path":["11552"],"owner":"44499","recid":"232748","title":["Panoptic Liftingにおける破滅的忘却を考慮した画像取捨選択による増分学習法"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-02-25"},"_buckets":{"deposit":"dd3c8190-ab56-4d40-9b39-b86bf7d5faf0"},"_deposit":{"id":"232748","pid":{"type":"depid","value":"232748","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"Panoptic Liftingにおける破滅的忘却を考慮した画像取捨選択による増分学習法","author_link":["630802","630801","630803","630804"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Panoptic Liftingにおける破滅的忘却を考慮した画像取捨選択による増分学習法"}]},"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":"滋賀大学大学院データサイエンス研究科／理化学研究所ガーディアンロボットプロジェクト"},{"subitem_text_value":"理化学研究所ガーディアンロボットプロジェクト"},{"subitem_text_value":"滋賀大学大学院データサイエンス研究科"},{"subitem_text_value":"理化学研究所ガーディアンロボットプロジェクト"}]},"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/232748/files/IPSJ-CVIM24237057.pdf","label":"IPSJ-CVIM24237057.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CVIM24237057.pdf","filesize":[{"value":"3.6 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"20"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"39a5505a-1112-4ec8-a625-361905f65314","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":"幸壬, 晃"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"薗頭, 元春"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"飯山, 将晃"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"川西, 康友"}],"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":"任意視点における RGB 画像とセグメンテーションマスクの再構成において Panoptic Lifting は強力な手法だが, ある箇所の画像データの不足がみられた際は, それらを追加したうえで再度モデルを構築する必要がある．そこで本稿では，計算量を抑えながら十分な精度のモデルを構築するための Panoptic Lifting の増分学習法を提案する．また，最小限の学習用画像で増分学習するため，破滅的忘却の抑制を考慮した画像の取捨選択法を導入する．位置的に等間隔な視点で撮影した画像を選択することにより，増分学習におけるセグメンテーションの精度向上を確認した．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","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":"57","bibliographicVolumeNumber":"2024-CVIM-237"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":232748,"updated":"2025-01-19T10:20:05.285943+00:00","links":{}}