{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00235986","sets":["6504:11678:11689"]},"path":["11689"],"owner":"44499","recid":"235986","title":["少量データから組立標準作業を判別する対照学習法の検討"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-03-01"},"_buckets":{"deposit":"c37bfee8-624f-46eb-8644-ffb65361c349"},"_deposit":{"id":"235986","pid":{"type":"depid","value":"235986","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"少量データから組立標準作業を判別する対照学習法の検討","author_link":["644913","644916","644915","644912","644917","644914"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"少量データから組立標準作業を判別する対照学習法の検討"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"人工知能と認知科学","subitem_subject_scheme":"Other"}]},"item_type_id":"22","publish_date":"2024-03-01","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":"静岡大"},{"subitem_text_value":"静岡大"},{"subitem_text_value":"愛知産大"},{"subitem_text_value":"ヤマハ発動機"},{"subitem_text_value":"ヤマハ発動機"},{"subitem_text_value":"ヤマハ発動機"}]},"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/235986/files/IPSJ-Z86-2Q-08.pdf","label":"IPSJ-Z86-2Q-08.pdf"},"date":[{"dateType":"Available","dateValue":"2024-07-03"}],"format":"application/pdf","filename":"IPSJ-Z86-2Q-08.pdf","filesize":[{"value":"774.6 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"945b1bf4-1ce1-49f0-b30d-f48a78238ca9","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"上山, 太郎"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"山本, 泰生"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"西村, 雅史"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"白澤, 怜樹"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"中野, 貴行"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"青木, 崇浩"}],"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":"本研究では，熟練度の判別を目的として，細かい作業動作を指示通りに実施できているかを判定する機械学習モデルを提案する．工程内の作業動作は指示書により定義されている．現場の作業者には定義された作業動作を正しく安定して実施することが求められる．定義された作業動作を正常に実施する作業を標準作業と呼ぶ．標準作業を高精度に判別できるモデルを構築できれば，教育現場における作業教育の改善が見込める．しかし標準作業として許容される動作範囲は曖昧であり，標準作業の観点から目視により全てのデータに対して明確なラベルを付与することは難しく労力もかかる．そのため，一般的な教師あり学習を用いることは適切でないと考えられる．そこで本研究では対照学習を用いた半教師あり学習のフレームワークを活用して，少量のラベル付きデータから高精度での標準作業の判別を可能にするモデルの構築を図る．本研究ではバイクの外装部品を取り付ける実際の製造工程を模した組立作業を対象とする．作業者の頭と両手首に装着したIMUによりセンシングした加速度・角速度の時系列データを使用して，提案手法の有用性を実証的に評価する．","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"286","bibliographic_titles":[{"bibliographic_title":"第86回全国大会講演論文集"}],"bibliographicPageStart":"285","bibliographicIssueDates":{"bibliographicIssueDate":"2024-03-01","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2024"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":235986,"updated":"2025-01-19T09:26:24.195326+00:00","links":{},"created":"2025-01-19T01:37:47.607266+00:00"}