{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00041153","sets":["1164:3616:3632:3633"]},"path":["3633"],"owner":"1","recid":"41153","title":["Facial Expression Recognition by Supervised ICA with Selective Prior"],"pubdate":{"attribute_name":"公開日","attribute_value":"2005-12-12"},"_buckets":{"deposit":"bc9c3b1e-34a6-4e50-bdbb-d331e8da86e5"},"_deposit":{"id":"41153","pid":{"type":"depid","value":"41153","revision_id":0},"owners":[1],"status":"published","created_by":1},"item_title":"Facial Expression Recognition by Supervised ICA with Selective Prior","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Facial Expression Recognition by Supervised ICA with Selective Prior"},{"subitem_title":"Facial Expression Recognition by Supervised ICA with Selective Prior","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2005-12-12","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"School of Information Science  Japan Advanced Institute of Science and Technology"},{"subitem_text_value":" School of Information Science  Japan Advanced Institute of Science and Technology"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"School of Information Science, Japan Advanced Institute of Science and Technology","subitem_text_language":"en"},{"subitem_text_value":" School of Information Science, Japan Advanced Institute of Science and Technology","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"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/41153/files/IPSJ-AVM05051006.pdf"},"date":[{"dateType":"Available","dateValue":"2007-12-12"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-AVM05051006.pdf","filesize":[{"value":"769.1 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"27"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"31476556-2449-4e40-a93e-6d482ca0a6d5","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2005 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Fan, Chen"},{"creatorName":"Kazunori, Kotani"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Fan, Chen","creatorNameLang":"en"},{"creatorName":"KazunoriKotani","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10438399","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_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"Feature selection is required when using the Independent Component Analysis (ICA) in feature extraction for pattern classification. Selection during ICA might provide a better candidate set of features. We propose a supervised ICA with a selective prior for the de-mixing coefficients so that those features with higher significance in discrimination could emerge easier during the learning. We formulate the learning rule for the supervised ICA in a form of the natural gradient approach and develop the algorithm of supervised ICA in facial expression analysis. The efficiency of the proposed algorithm has been investigated by numerical experiments.","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Feature selection is required when using the Independent Component Analysis (ICA) in feature extraction for pattern classification. Selection during ICA might provide a better candidate set of features. We propose a supervised ICA with a selective prior for the de-mixing coefficients so that those features with higher significance in discrimination could emerge easier during the learning. We formulate the learning rule for the supervised ICA in a form of the natural gradient approach and develop the algorithm of supervised ICA in facial expression analysis. The efficiency of the proposed algorithm has been investigated by numerical experiments.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"32","bibliographic_titles":[{"bibliographic_title":"情報処理学会研究報告オーディオビジュアル複合情報処理（AVM）"}],"bibliographicPageStart":"27","bibliographicIssueDates":{"bibliographicIssueDate":"2005-12-12","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"124(2005-AVM-051)","bibliographicVolumeNumber":"2005"}]},"relation_version_is_last":true,"weko_creator_id":"1"},"id":41153,"updated":"2025-01-22T12:04:45.332214+00:00","links":{},"created":"2025-01-18T23:08:05.643542+00:00"}