{"created":"2025-01-19T01:29:12.863219+00:00","updated":"2025-01-19T11:24:14.883092+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00229822","sets":["6504:11436:11440"]},"path":["11440"],"owner":"44499","recid":"229822","title":["製造現場のAI画像検査における精度低下の自動検知"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-02-16"},"_buckets":{"deposit":"18a48de7-398d-4bee-9293-f83b94f0ec09"},"_deposit":{"id":"229822","pid":{"type":"depid","value":"229822","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"製造現場のAI画像検査における精度低下の自動検知","author_link":["618210","618208","618211","618207","618209"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"製造現場のAI画像検査における精度低下の自動検知"}]},"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":"2023-02-16","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":"東芝"},{"subitem_text_value":"東芝"},{"subitem_text_value":"東芝"},{"subitem_text_value":"東芝マテリアル株式会社"},{"subitem_text_value":"東芝マテリアル株式会社"}]},"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/229822/files/IPSJ-Z85-4C-02.pdf","label":"IPSJ-Z85-4C-02.pdf"},"date":[{"dateType":"Available","dateValue":"2023-11-17"}],"format":"application/pdf","filename":"IPSJ-Z85-4C-02.pdf","filesize":[{"value":"653.4 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"ba2fa878-42b4-444f-9bc0-7f6fc9aaf649","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2023 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"林, 恭太朗"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"内田, 美幸"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"鷲谷, 泰佑"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"山田, 勝彦"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"秋元, 俊之"}],"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":"AI画像検査は、従来の画像処理と比べて定性的な判定の自動化が容易となり、高精度な検査が可能となるため、近年製造現場への導入が増加している。しかし、AI画像検査は、運用当初は高い検査精度であっても、製品状態や製造プロセスの経時変化に伴って検査精度が低下する問題がある。検査精度の低下は不良品流出につながる可能性があるため、早期に検知する必要がある。そこで、検査精度のモニタリング技術として、特徴量空間上で運用当初の特徴量分布からの逸脱を検知する手法を開発した。これを弊社セラミック製品製造現場のAI画像検査に適用した結果、製造現場における検査精度に影響する経時変化を早期に検知可能であることを確認した。","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"42","bibliographic_titles":[{"bibliographic_title":"第85回全国大会講演論文集"}],"bibliographicPageStart":"41","bibliographicIssueDates":{"bibliographicIssueDate":"2023-02-16","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2023"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":229822,"links":{}}