{"links":{},"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00220654","sets":["6504:11035:11037"]},"path":["11037"],"owner":"44499","recid":"220654","title":["覚醒低下検出モデルにおけるVariational Autoencoderの潜在空間の次元数最適化"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-02-17"},"_buckets":{"deposit":"1f608531-630d-499c-bf22-d241664f3360"},"_deposit":{"id":"220654","pid":{"type":"depid","value":"220654","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"覚醒低下検出モデルにおけるVariational Autoencoderの潜在空間の次元数最適化","author_link":["577332","577329","577330","577331","577328"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"覚醒低下検出モデルにおけるVariational Autoencoderの潜在空間の次元数最適化"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"ソフトウェア科学・工学","subitem_subject_scheme":"Other"}]},"item_type_id":"22","publish_date":"2022-02-17","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":"青学大"},{"subitem_text_value":"青学大"},{"subitem_text_value":"青学大"},{"subitem_text_value":"青学大"},{"subitem_text_value":"青学大"}]},"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/220654/files/IPSJ-Z84-2M-07.pdf","label":"IPSJ-Z84-2M-07.pdf"},"date":[{"dateType":"Available","dateValue":"2022-10-22"}],"format":"application/pdf","filename":"IPSJ-Z84-2M-07.pdf","filesize":[{"value":"448.1 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"a94b192b-e3ee-4c45-90ac-6da973002cad","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2022 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"松井, 恵莉香"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"高野, 聖人"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"南雲, 健人"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"大岩, 孝輔"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"野澤, 昭雄"}],"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":"近年、自動運転の実用化に向けて研究が進んでいる。ドライバーは緊急時の運転操作のために覚醒度を維持する必要があり、覚醒低下検出技術の開発が求められている。これまで、時系列変化を捉えて覚醒低下を検出する方法が提案されてきたが、覚醒低下検出に時間を要することが課題である。そこで我々は、時間的情報を用いず顔面皮膚温度分布の情報を利用することで、短時間で覚醒低下検出をできると考えた。本研究では，VAEを用いて一過性覚醒低下検出のための一般モデルを構築した。しかし、モデルの精度にばらつきがあったため、VAEにおける最適な潜在空間の次元数を探索した。","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"380","bibliographic_titles":[{"bibliographic_title":"第84回全国大会講演論文集"}],"bibliographicPageStart":"379","bibliographicIssueDates":{"bibliographicIssueDate":"2022-02-17","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2022"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T01:20:41.195556+00:00","updated":"2025-01-19T14:29:03.772073+00:00","id":220654}