{"id":109905,"updated":"2025-01-21T08:07:22.910065+00:00","links":{},"created":"2025-01-18T23:52:16.456429+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00109905","sets":["6504:6739:7816"]},"path":["7816"],"owner":"6748","recid":"109905","title":["変分ベイズ法を用いた分離型2次元格子HMMの学習におけるアニーリング制御の適用"],"pubdate":{"attribute_name":"公開日","attribute_value":"2012-03-06"},"_buckets":{"deposit":"1021aac3-15f6-4b19-ae7e-d59e04126bb1"},"_deposit":{"id":"109905","pid":{"type":"depid","value":"109905","revision_id":0},"owners":[6748],"status":"published","created_by":6748},"item_title":"変分ベイズ法を用いた分離型2次元格子HMMの学習におけるアニーリング制御の適用","author_link":["25161","25162","25160","25163","25164"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"変分ベイズ法を用いた分離型2次元格子HMMの学習におけるアニーリング制御の適用"}]},"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":"2012-03-06","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":"名工大"},{"subitem_text_value":"名工大"},{"subitem_text_value":"名工大"},{"subitem_text_value":"名工大"},{"subitem_text_value":"名工大"}]},"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/109905/files/IPSJ-Z74-5S-7.pdf"},"date":[{"dateType":"Available","dateValue":"2014-12-18"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-Z74-5S-7.pdf","filesize":[{"value":"114.9 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"e4611d3e-1dcd-4b9e-a9c3-98948e6d9e79","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2012 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"沢田慶"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"玉森聡"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"橋本佳"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"南角吉彦"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"徳田恵一"}],"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":"画像認識において，認識対象の位置や大きさの変動に対応するための手法として分離型2次元格子HMM(SL2D-HMM)に基づく画像認識が提案されている．SL2D-HMMの学習基準を尤度最大化基準からベイズ基準にすることで汎化能力の向上が確認された．しかし，ベイズ基準に用いられる学習アルゴリズムは，推定結果が初期値に依存するという局所最適性の問題を有する．この問題を改善する手法として，確定的アニーリングEM(DAEM)アルゴリズムがある．そこで，本稿では変分ベイズ法を用いたSL2D-HMMの学習にDAEMアルゴリズムを適用し，顔画像認識実験により提案法の有効性を確認する．","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"410","bibliographic_titles":[{"bibliographic_title":"第74回全国大会講演論文集"}],"bibliographicPageStart":"409","bibliographicIssueDates":{"bibliographicIssueDate":"2012-03-06","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2012"}]},"relation_version_is_last":true,"weko_creator_id":"6748"}}