{"created":"2025-01-19T01:29:21.341429+00:00","updated":"2025-01-19T11:22:01.850356+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00229910","sets":["6504:11436:11440"]},"path":["11440"],"owner":"44499","recid":"229910","title":["ドメイン適応による撮影環境に対して頑健な植物病害診断システムの構築"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-02-16"},"_buckets":{"deposit":"644cba38-cc71-424d-b641-61f8ac24ab34"},"_deposit":{"id":"229910","pid":{"type":"depid","value":"229910","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"ドメイン適応による撮影環境に対して頑健な植物病害診断システムの構築","author_link":["618486"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"ドメイン適応による撮影環境に対して頑健な植物病害診断システムの構築"}]},"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":"法大"}]},"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/229910/files/IPSJ-Z85-4Q-05.pdf","label":"IPSJ-Z85-4Q-05.pdf"},"date":[{"dateType":"Available","dateValue":"2023-11-17"}],"format":"application/pdf","filename":"IPSJ-Z85-4Q-05.pdf","filesize":[{"value":"242.7 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"d4eb931c-e44e-40e2-8b45-472287399aa3","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":"工藤, 渉真"}],"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":"農業現場において簡便な植物病害自動診断システムが求められている. 近年, 深層学習に基づく植物病害診断システムが複数提案されており, いずれも高い精度を達成している. しかし, 対象自体の外見や栽培方法などの環境, 画角や機器など様々な条件が, 圃場(ドメイン)により大きく異なり, これらの差が一般に病害特徴より大きいため, 未知の撮影環境の画像に対して精度が大きく低下する. 本報告では, ドメイン差の影響を軽減し, 検出すべき病徴の差に, より着目する学習を導入することで, 頑健で実用的な植物病害診断システムを構築する. また, ドメイン適応学習が病害の識別精度に与える影響を調査し報告する.","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"224","bibliographic_titles":[{"bibliographic_title":"第85回全国大会講演論文集"}],"bibliographicPageStart":"223","bibliographicIssueDates":{"bibliographicIssueDate":"2023-02-16","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2023"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":229910,"links":{}}