{"links":{},"id":229943,"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00229943","sets":["6504:11436:11440"]},"path":["11440"],"owner":"44499","recid":"229943","title":["マスク着用顔画像の表情認識を目的としたSCN-SAMの提案"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-02-16"},"_buckets":{"deposit":"f8f9fdd2-a42f-4903-af9f-70bc4b843870"},"_deposit":{"id":"229943","pid":{"type":"depid","value":"229943","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"マスク着用顔画像の表情認識を目的としたSCN-SAMの提案","author_link":["618602","618601","618603"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"マスク着用顔画像の表情認識を目的としたSCN-SAMの提案"}]},"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":"帝京大"},{"subitem_text_value":"帝京大"},{"subitem_text_value":"帝京大"}]},"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/229943/files/IPSJ-Z85-1R-05.pdf","label":"IPSJ-Z85-1R-05.pdf"},"date":[{"dateType":"Available","dateValue":"2023-11-17"}],"format":"application/pdf","filename":"IPSJ-Z85-1R-05.pdf","filesize":[{"value":"518.7 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"7ea68309-c040-4899-8402-d4b0808aad7a","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":"呉, 強"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"荒井, 正之"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"浜田, 宏一"}],"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":"Due to COVID-19, wearing masks has become more common. However, it is challenging to recognize expressions in the images of people wearing masks. In general facial recognition problems, blurred images and incorrect annotations of images in large-scale image datasets can make the model’s training difficult, which can lead to degraded recognition performance. To address this problem, this paper verifies the recognition ability of Self-Cure Network (SCN) on images of people wearing masks and proposes a self-adjustment module to further improve SCN (called SCN-SAM). We experimentally demonstrate the effectiveness of SCN on the masked facial expression dataset and demonstrate that SCN-SAM outperforms state-of-the-art methods in synthetic noise-added FER datasets.","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"292","bibliographic_titles":[{"bibliographic_title":"第85回全国大会講演論文集"}],"bibliographicPageStart":"291","bibliographicIssueDates":{"bibliographicIssueDate":"2023-02-16","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2023"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T01:29:24.382398+00:00","updated":"2025-01-19T11:21:11.320132+00:00"}