{"id":213176,"updated":"2025-01-19T17:14:42.119177+00:00","links":{},"created":"2025-01-19T01:14:05.124825+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00213176","sets":["934:6391:10519:10652"]},"path":["10652"],"owner":"44499","recid":"213176","title":["Person Identification Based on Accelerations Sensed in Smartphones with LSTM (Preprint)"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-09-30"},"_buckets":{"deposit":"adee1106-782b-42b5-bdf2-6cd000422167"},"_deposit":{"id":"213176","pid":{"type":"depid","value":"213176","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"Person Identification Based on Accelerations Sensed in Smartphones with LSTM (Preprint)","author_link":["544961","544953","544952","544958","544960","544954","544955","544959","544957","544956"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Person Identification Based on Accelerations Sensed in Smartphones with LSTM (Preprint)"},{"subitem_title":"Person Identification Based on Accelerations Sensed in Smartphones with LSTM (Preprint)","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"[研究論文] accelerometer, machine learning, LSTM, personal identification","subitem_subject_scheme":"Other"}]},"item_type_id":"3","publish_date":"2021-09-30","item_3_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"Kogakuin University"},{"subitem_text_value":"Kogakuin University"},{"subitem_text_value":"Nagasaki University"},{"subitem_text_value":"Ochanomizu University"},{"subitem_text_value":"Kogakuin University"}]},"item_3_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Kogakuin University","subitem_text_language":"en"},{"subitem_text_value":"Kogakuin University","subitem_text_language":"en"},{"subitem_text_value":"Nagasaki University","subitem_text_language":"en"},{"subitem_text_value":"Ochanomizu University","subitem_text_language":"en"},{"subitem_text_value":"Kogakuin University","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":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/213176/files/IPSJ-TCDS1103005.pdf","label":"IPSJ-TCDS1103005.pdf"},"date":[{"dateType":"Available","dateValue":"2023-09-30"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-TCDS1103005.pdf","filesize":[{"value":"2.2 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":"47"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"570347b5-f038-4346-8451-8e93497a5a88","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2021 by the Information Processing Society of Japan"}]},"item_3_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Yoshihaya, Takahashi"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Kosuke, Nakamura"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takeshi, Kamiyama"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Masato, Oguchi"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Saneyasu, Yamaguchi"}],"nameIdentifiers":[{}]}]},"item_3_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Yoshihaya, Takahashi","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Kosuke, Nakamura","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takeshi, Kamiyama","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Masato, Oguchi","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Saneyasu, Yamaguchi","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_3_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA12628043","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":"2186-5728","subitem_source_identifier_type":"ISSN"}]},"item_3_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"User identification is an important task for a variety of purposes such as authentication or providing personalized advice for improving user experience. In this paper, we propose a method for identifying a user who is holding a smartphone out of previously given target users from acceleration data obtained from the accelerometer in the smartphone using a deep neural network. This proposed method preliminary creates the model from the acceleration data of each user while walking in its training phase. This method identifies the user from acceleration data for identification based on this model in the classification phase. We evaluated the proposed method with the acceleration obtained from the actual eight and twelve users in two aspects, which were identifications including no-decision choice and that without no-decision choice. Our evaluation showed that the proposed method achieved accuracies higher than 95% for two- to five-class identification without no-decision. The proposed method identified the user with no or little false positive in evaluations with “no-decision.”\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.29(2021) (online)\n------------------------------","subitem_description_type":"Other"}]},"item_3_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"User identification is an important task for a variety of purposes such as authentication or providing personalized advice for improving user experience. In this paper, we propose a method for identifying a user who is holding a smartphone out of previously given target users from acceleration data obtained from the accelerometer in the smartphone using a deep neural network. This proposed method preliminary creates the model from the acceleration data of each user while walking in its training phase. This method identifies the user from acceleration data for identification based on this model in the classification phase. We evaluated the proposed method with the acceleration obtained from the actual eight and twelve users in two aspects, which were identifications including no-decision choice and that without no-decision choice. Our evaluation showed that the proposed method achieved accuracies higher than 95% for two- to five-class identification without no-decision. The proposed method identified the user with no or little false positive in evaluations with “no-decision.”\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.29(2021) (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コンシューマ・デバイス＆システム（CDS）"}],"bibliographicIssueDates":{"bibliographicIssueDate":"2021-09-30","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"3","bibliographicVolumeNumber":"11"}]},"relation_version_is_last":true,"weko_creator_id":"44499"}}