{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00216935","sets":["1164:4619:10826:10881"]},"path":["10881"],"owner":"44499","recid":"216935","title":["加重方程式の最適解に基づくパターン認識系の構成について"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-03-03"},"_buckets":{"deposit":"1f58fee9-e7ae-4d0a-bc7e-23c8c4550372"},"_deposit":{"id":"216935","pid":{"type":"depid","value":"216935","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"加重方程式の最適解に基づくパターン認識系の構成について","author_link":["561019"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"加重方程式の最適解に基づくパターン認識系の構成について"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"セッション1-A","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2022-03-03","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"日本女子大学理学部数物科学科"}]},"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/216935/files/IPSJ-CVIM22229004.pdf","label":"IPSJ-CVIM22229004.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CVIM22229004.pdf","filesize":[{"value":"1.7 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"20"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"eed83fee-4a1a-41f8-ac76-e3d5721acdc1","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2022 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":"尺長, 健"}],"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":"本稿では，加重和制約付き加重方程式の最適解に基づくパターン認識系の構成について述べる．従来，不足決定系においては，加重和制約により最適解が白色化後の内積計算に帰着されることを示した．また，白色化後に  閾値処理を施すことにより，高性能な認識系を実現できることを示した．本稿では，過剰決定系における最適解と白色化との関係を示すとともに，白色化後の閾値処理の有効性を示す．また，関連技術との関係を論じる．","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":"2022-03-03","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"4","bibliographicVolumeNumber":"2022-CVIM-229"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":216935,"updated":"2025-01-19T15:40:55.247797+00:00","links":{},"created":"2025-01-19T01:17:26.787393+00:00"}