{"created":"2025-01-19T01:29:12.959936+00:00","updated":"2025-01-19T11:24:12.780346+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00229823","sets":["6504:11436:11440"]},"path":["11440"],"owner":"44499","recid":"229823","title":["AI画像検査における中間層データを用いた再学習時間の短縮"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-02-16"},"_buckets":{"deposit":"35d7977f-7b7a-4963-be58-3f39e00e0fc6"},"_deposit":{"id":"229823","pid":{"type":"depid","value":"229823","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"AI画像検査における中間層データを用いた再学習時間の短縮","author_link":["618212","618213"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"AI画像検査における中間層データを用いた再学習時間の短縮"}]},"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"}]},"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/229823/files/IPSJ-Z85-4C-03.pdf","label":"IPSJ-Z85-4C-03.pdf"},"date":[{"dateType":"Available","dateValue":"2023-11-17"}],"format":"application/pdf","filename":"IPSJ-Z85-4C-03.pdf","filesize":[{"value":"769.6 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"44ab6de2-d0b7-41b8-99a3-227a21b8a660","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":"内田, 美幸"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"鷲谷, 泰佑"}],"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":"製造現場におけるAI画像検査の精度低下は不良品流出につながるため、早期の検査精度回復が必要となる。一般に、既存の学習データに新たな学習データを加えてAIモデルを再学習することで、検査精度を回復できる。しかし、データの蓄積により学習データ量が増大し、再学習に1週間以上の時間を要する場合もあり、効率的な再学習技術が求められている。そこで、再学習時間を短縮する技術として、画像の特徴が数値化されているAIモデルの中間層データを活用し、学習データの多様な特徴を効率的に学習する手法を開発した。開発した学習手法を実際のAI画像検査へ適用した結果、再学習に要する時間を半減可能なことを確認した。","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"44","bibliographic_titles":[{"bibliographic_title":"第85回全国大会講演論文集"}],"bibliographicPageStart":"43","bibliographicIssueDates":{"bibliographicIssueDate":"2023-02-16","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2023"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":229823,"links":{}}