{"updated":"2025-01-20T06:55:33.785334+00:00","links":{},"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00158446","sets":["934:1022:8505:8506"]},"path":["8506"],"owner":"11","recid":"158446","title":["Dictionary learning by Normalized Bilateral Projection"],"pubdate":{"attribute_name":"公開日","attribute_value":"2016-03-31"},"_buckets":{"deposit":"a19d645c-2ec9-46d6-b5b0-251bfe7f9fec"},"_deposit":{"id":"158446","pid":{"type":"depid","value":"158446","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"Dictionary learning by Normalized Bilateral Projection","author_link":["303179","303178"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Dictionary learning by Normalized Bilateral Projection"},{"subitem_title":"Dictionary learning by Normalized Bilateral Projection","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"[研究論文] dictionary learning, sparse coding, bilateral projections, image reconstruction","subitem_subject_scheme":"Other"}]},"item_type_id":"3","publish_date":"2016-03-31","item_3_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"University of Tsukuba"}]},"item_3_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"University of Tsukuba","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":11,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/158446/files/IPSJ-TOD0901003.pdf","label":"IPSJ-TOD0901003.pdf"},"date":[{"dateType":"Available","dateValue":"2018-03-31"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-TOD0901003.pdf","filesize":[{"value":"1.1 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"5"},{"tax":["include_tax"],"price":"0","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"13"},{"tax":["include_tax"],"price":"0","billingrole":"39"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"5633a4f5-6c4a-40b7-804a-f304b706d579","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2016 by the Information Processing Society of Japan"}]},"item_3_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Taro, Tezuka"}],"nameIdentifiers":[{}]}]},"item_3_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Taro, Tezuka","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_3_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11464847","subitem_source_identifier_type":"NCID"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_6501","resourcetype":"journal article"}]},"item_3_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"1882-7799","subitem_source_identifier_type":"ISSN"}]},"item_3_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"Dictionary learning is an unsupervised learning task that finds a set of template vectors that expresses input signals by sparse linear combinations. There are currently several methods for dictionary learning, for example K-SVD and MOD. In this paper, a new dictionary learning method, namely K-normalized bilateral projections (K-NBP), is proposed, which uses faster low rank approximation. Experiments showed that the method was fast and when the number of iterations was limited, it outperforms K-SVD. This indicated that the method was particularly suited to large data sets with high dimension, where each iteration takes a long time. K-NBP was applied to an image reconstruction task where images corrupted by noise were recovered using a dictionary learned from other images.\n\\n------------------------------\nThis is a preprint of an article intended for publication Journal of\nInformation Processing(JIP). This preprint should not be cited. This\narticle should be cited as: Journal of Information Processing Vol.24(2016) No.3(online)\n------------------------------","subitem_description_type":"Other"}]},"item_3_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Dictionary learning is an unsupervised learning task that finds a set of template vectors that expresses input signals by sparse linear combinations. There are currently several methods for dictionary learning, for example K-SVD and MOD. In this paper, a new dictionary learning method, namely K-normalized bilateral projections (K-NBP), is proposed, which uses faster low rank approximation. Experiments showed that the method was fast and when the number of iterations was limited, it outperforms K-SVD. This indicated that the method was particularly suited to large data sets with high dimension, where each iteration takes a long time. K-NBP was applied to an image reconstruction task where images corrupted by noise were recovered using a dictionary learned from other images.\n\\n------------------------------\nThis is a preprint of an article intended for publication Journal of\nInformation Processing(JIP). This preprint should not be cited. This\narticle should be cited as: Journal of Information Processing Vol.24(2016) No.3(online)\n------------------------------","subitem_description_type":"Other"}]},"item_3_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographic_titles":[{"bibliographic_title":"情報処理学会論文誌データベース（TOD）"}],"bibliographicIssueDates":{"bibliographicIssueDate":"2016-03-31","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"9"}]},"relation_version_is_last":true,"weko_creator_id":"11"},"id":158446,"created":"2025-01-19T00:32:08.644945+00:00"}