{"id":217452,"updated":"2025-01-19T15:29:37.692992+00:00","links":{},"created":"2025-01-19T01:17:56.581715+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00217452","sets":["1164:3027:10764:10847"]},"path":["10847"],"owner":"44499","recid":"217452","title":["画像データによる温熱快適度推定手法のためのウェアラブルセンサデータを用いた半教師あり学習手法"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-03-07"},"_buckets":{"deposit":"9b029feb-da07-4ff5-8c52-b10b5431b877"},"_deposit":{"id":"217452","pid":{"type":"depid","value":"217452","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"画像データによる温熱快適度推定手法のためのウェアラブルセンサデータを用いた半教師あり学習手法","author_link":["563478","563477","563471","563474","563475","563472","563473","563476"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"画像データによる温熱快適度推定手法のためのウェアラブルセンサデータを用いた半教師あり学習手法"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"データ分析とシステム開発","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2022-03-07","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"神戸大学大学院工学研究科"},{"subitem_text_value":"神戸大学大学院工学研究科"},{"subitem_text_value":"ソフトバンク株式会社"},{"subitem_text_value":"ソフトバンク株式会社"},{"subitem_text_value":"ソフトバンク株式会社"},{"subitem_text_value":"ソフトバンク株式会社"},{"subitem_text_value":"神戸大学大学院工学研究科"},{"subitem_text_value":"神戸大学大学院工学研究科"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Engineering, Kobe University","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Engineering, Kobe University","subitem_text_language":"en"},{"subitem_text_value":"SoftBank Corp.","subitem_text_language":"en"},{"subitem_text_value":"SoftBank Corp.","subitem_text_language":"en"},{"subitem_text_value":"SoftBank Corp.","subitem_text_language":"en"},{"subitem_text_value":"SoftBank Corp.","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Engineering, Kobe University","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Engineering, Kobe University","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 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Haomin"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"土田, 修平"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"鈴木, 裕真"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Kim, Yongbeom"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"金田, 麟太郎"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"堀, 隆之"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"寺田, 努"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"塚本, 昌彦"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA1221543X","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":"2188-8760","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"日常生活における快適な環境を構築するためには，人が感じる温熱快適度を適切に推定することが重要である．温熱快適度を取得する手法として，アンケートで回答してもらう手法が挙げられるが，日常生活において室内温度を変化させる度にアンケートを実施することは難しい．日常生活での温熱快適度を推定したい場合，ウェアラブルセンサから得られるデータまたはカメラから得られる画像データによる推定手法が考えられる．ウェアラブルセンサを用いて温熱快適度を推定する場合，部屋内にいる人がウェアラブルセンサを装着する必要があり，温熱快適度を活用したシステムの恩恵を受けられる対象が狭まる．画像データを用いる場合は，部屋内にカメラを配置することで画像データを容易に取得できる．しかし，アンケートの回答により取得できる温熱快適度のラベル付き画像データを大量に収集することは難しい．そこで本研究では，画像データと同じタイミングで取得したウェアラブルセンサデータによりラベルなしの画像データにラベルを付与することで，温熱快適度推定のための半教師あり学習を行う手法を提案した．また，提案手法により温熱快適度の推定結果と半教師あり学習の代表手法の Self-training により温熱快適度の推定結果を比較し，提案手法の推定精度が高いことが判明した．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"8","bibliographic_titles":[{"bibliographic_title":"研究報告ヒューマンコンピュータインタラクション（HCI）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2022-03-07","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"33","bibliographicVolumeNumber":"2022-HCI-197"}]},"relation_version_is_last":true,"weko_creator_id":"44499"}}