{"created":"2025-01-19T01:29:24.291265+00:00","updated":"2025-01-19T11:21:12.734804+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00229942","sets":["6504:11436:11440"]},"path":["11440"],"owner":"44499","recid":"229942","title":["3表情を対象とした表情認識モデルにおける警戒パラメータの決定法に関する検討"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-02-16"},"_buckets":{"deposit":"1e1c8d6c-4615-45c8-8da2-3e90a3ca6c5f"},"_deposit":{"id":"229942","pid":{"type":"depid","value":"229942","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"3表情を対象とした表情認識モデルにおける警戒パラメータの決定法に関する検討","author_link":["618598","618600","618599"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"3表情を対象とした表情認識モデルにおける警戒パラメータの決定法に関する検討"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"人工知能と認知科学","subitem_subject_scheme":"Other"}]},"item_type_id":"22","publish_date":"2023-02-16","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_22_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"秋田大"},{"subitem_text_value":"秋田県大"},{"subitem_text_value":"秋田大"}]},"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/229942/files/IPSJ-Z85-1R-04.pdf","label":"IPSJ-Z85-1R-04.pdf"},"date":[{"dateType":"Available","dateValue":"2023-11-17"}],"format":"application/pdf","filename":"IPSJ-Z85-1R-04.pdf","filesize":[{"value":"635.1 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"d3bc6998-e9c3-4dc6-8d54-ed928b787062","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2023 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"高松, 未佳"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"石井, 雅樹"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"景山, 陽一"}],"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_22_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00349328","subitem_source_identifier_type":"NCID"}]},"item_22_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"人間の感情を認識するとき，コミュニケーションにおいて重要な役割を担う表情に着目することが有効である．人間が表出する表情パターンは多様であるのに加えて，時間経過に伴って新たなパターンが出現することも考えられる．したがって，表情認識モデルには，未学習のパターンに適応して進化する機能が求められる．本研究ではこれまでに，CPNとFuzzy-ARTを組み合わせた追加学習機能を有する表情認識モデルを提案した．しかしながら，追加学習を行ったところ，表情を誤って学習したことに起因して表情認識の精度が低下する場合を認めた．そこで本稿では，追加学習処理を決定する際の判断基準である警戒パラメータに関する検討を行った．","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"290","bibliographic_titles":[{"bibliographic_title":"第85回全国大会講演論文集"}],"bibliographicPageStart":"289","bibliographicIssueDates":{"bibliographicIssueDate":"2023-02-16","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2023"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":229942,"links":{}}