{"created":"2021-03-01T06:18:57.090707+00:00","id":12020,"links":{},"metadata":{"_buckets":{"deposit":"7abb5a7c-b7cc-4171-899f-b6dd9e2ae4f9"},"_deposit":{"id":"12020","owners":[],"pid":{"revision_id":0,"type":"depid","value":"12020"},"status":"published"},"_oai":{"id":"oai:nagoya.repo.nii.ac.jp:00012020","sets":["320:321:322"]},"author_link":["38104","38105","38106","38107"],"item_10_biblio_info_6":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2009-10-11","bibliographicIssueDateType":"Issued"},"bibliographicPageEnd":"533","bibliographicPageStart":"529","bibliographic_titles":[{"bibliographic_title":"IEEE International Conference on Systems, Man and Cybernetics (SMC 2009)","bibliographic_titleLang":"en"}]}]},"item_10_description_4":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"Most conventional methods of feature extraction for pattern recognition do not pay sufficient attention to inherent geometric properties of data, even in the case where the data have spatial features. This paper introduces geometric algebra to extract invariant geometric features from spatial data given in a vector space. Geometric algebra is a multidimensional generalization of complex numbers and of quaternions, and it ables to accurately describe oriented spatial objects and relations between them. This paper proposes to combine several geometric features using Gaussian mixture models. It applies the proposed method to the classification of hand-written digits.","subitem_description_language":"en","subitem_description_type":"Abstract"}]},"item_10_identifier_60":{"attribute_name":"URI","attribute_value_mlt":[{"subitem_identifier_type":"HDL","subitem_identifier_uri":"http://hdl.handle.net/2237/13896"},{"subitem_identifier_type":"DOI","subitem_identifier_uri":"http://dx.doi.org/10.1109/ICSMC.2009.5346869"}]},"item_10_publisher_32":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"IEEE","subitem_publisher_language":"en"}]},"item_10_relation_11":{"attribute_name":"DOI","attribute_value_mlt":[{"subitem_relation_type":"isVersionOf","subitem_relation_type_id":{"subitem_relation_type_id_text":"https://doi.org/10.1109/ICSMC.2009.5346869","subitem_relation_type_select":"DOI"}}]},"item_10_rights_12":{"attribute_name":"権利","attribute_value_mlt":[{"subitem_rights":"©2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.","subitem_rights_language":"en"}]},"item_10_select_15":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_select_item":"author"}]},"item_10_source_id_7":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"1062-922X","subitem_source_identifier_type":"PISSN"}]},"item_10_text_14":{"attribute_name":"フォーマット","attribute_value_mlt":[{"subitem_text_value":"application/pdf"}]},"item_1615787544753":{"attribute_name":"出版タイプ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_ab4af688f83e57aa","subitem_version_type":"AM"}]},"item_access_right":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"open access","subitem_access_right_uri":"http://purl.org/coar/access_right/c_abf2"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Minh, Tuan  Pham","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"38104","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Yoshikawa, Tomohiro","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"38105","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Furuhashi, Takeshi","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"38106","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Tachibana, Kaita","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"38107","nameIdentifierScheme":"WEKO"}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2018-02-20"}],"displaytype":"detail","filename":"Robust_feature_extractions.pdf","filesize":[{"value":"690.7 kB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"Robust_feature_extractions.pdf","objectType":"fulltext","url":"https://nagoya.repo.nii.ac.jp/record/12020/files/Robust_feature_extractions.pdf"},"version_id":"f70894e9-1309-4cc0-b39b-600f302df81e"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"Feature extraction","subitem_subject_scheme":"Other"},{"subitem_subject":"Gaussian mixture model","subitem_subject_scheme":"Other"},{"subitem_subject":"Geometric Algebra","subitem_subject_scheme":"Other"},{"subitem_subject":"Pattern recognition","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"journal article","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"Robust feature extractions from geometric data using geometric algebra","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Robust feature extractions from geometric data using geometric algebra","subitem_title_language":"en"}]},"item_type_id":"10","owner":"1","path":["322"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2010-07-30"},"publish_date":"2010-07-30","publish_status":"0","recid":"12020","relation_version_is_last":true,"title":["Robust feature extractions from geometric data using geometric algebra"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2023-01-16T03:58:40.507844+00:00"}