{"links":{},"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00183445","sets":["1164:4619:9026:9245"]},"path":["9245"],"owner":"11","recid":"183445","title":["加速度データからの行動識別のための雑音除去自己符号化器を用いた特徴抽出"],"pubdate":{"attribute_name":"公開日","attribute_value":"2017-09-08"},"_buckets":{"deposit":"90c2383d-c75b-49bf-a1e8-4e826c8a7426"},"_deposit":{"id":"183445","pid":{"type":"depid","value":"183445","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"加速度データからの行動識別のための雑音除去自己符号化器を用いた特徴抽出","author_link":["402572","402569","402571","402570"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"加速度データからの行動識別のための雑音除去自己符号化器を用いた特徴抽出"},{"subitem_title":"Feature Extraction Using Denoising Autoencoders for Activity Recognition from Acceleration Data","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2017-09-08","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"金沢工業大学大学院工学研究科"},{"subitem_text_value":"金沢工業大学工学部"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Engineering, Kanazawa Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"College of Engineering, Kanazawa Institute of Technology","subitem_text_language":"en"}]},"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/183445/files/IPSJ-CVIM17208026.pdf","label":"IPSJ-CVIM17208026.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CVIM17208026.pdf","filesize":[{"value":"833.7 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"20"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"10b84150-b995-4e31-b719-bb89c13979e6","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2017 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":"武山, 徹"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"小暮, 潔"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Toru, Takeyama","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Kiyoshi, Kogure","creatorNameLang":"en"}],"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":"本研究では，加速度データからの行動識別のための雑音除去自己符号化器を用いた特徴抽出方法の性能を評価した．具体的には，加速度データからの積層雑音除去自己符号化器による特徴抽出における出力層のノード数，加速度データの取得部位の組み合わせ，および加速度データの与え方の行動識別の正解率への影響を実験によって評価した．実験結果は，単一部位の 3 軸加速度データから抽出した特徴に関する出力層のノード数による正解率の顕著な変化の傾向，および 6 部位の 3 軸加速度データから抽出した特徴に関する入力層のノード数以下の範囲内での出力層のノード数の増加に伴う正解率の単調増加性を示す．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"We have experimentally evaluated how the performance of activity recognition from acceleration data depends on the way of extracting features using denoising autoencoders. The experimental results show that when each of stacked denoising autoencoders is given 3-axis acceleration data from a body part, the accuracy of classification using their output features changes saliently according to the number of nodes in each of their output layers and that when a stacked denoising autoencoder is given 3-axis acceleration data from six body parts, the accuracy of classification monotonically increases with the increasing number of nodes in its output layer as long as the number is less than or equal to the number of nodes in its input layer.","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":"2017-09-08","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"26","bibliographicVolumeNumber":"2017-CVIM-208"}]},"relation_version_is_last":true,"weko_creator_id":"11"},"updated":"2025-01-20T03:40:31.824735+00:00","created":"2025-01-19T00:50:58.040134+00:00","id":183445}