{"links":{},"id":196839,"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00196839","sets":["6504:9795:9801"]},"path":["9801"],"owner":"6748","recid":"196839","title":["背景多様性の疑似拡張によるトマト自動診断への影響の調査"],"pubdate":{"attribute_name":"公開日","attribute_value":"2019-02-28"},"_buckets":{"deposit":"6896931c-4f2f-4d79-b9a5-53a545ef1290"},"_deposit":{"id":"196839","pid":{"type":"depid","value":"196839","revision_id":0},"owners":[6748],"status":"published","created_by":6748},"item_title":"背景多様性の疑似拡張によるトマト自動診断への影響の調査","author_link":["471452","471454","471453","471455"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"背景多様性の疑似拡張によるトマト自動診断への影響の調査"}]},"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":"2019-02-28","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"},{"subitem_text_value":"法大"},{"subitem_text_value":"法大"},{"subitem_text_value":"埼玉県農業技術研究センター"}]},"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/196839/files/IPSJ-Z81-1S-05.pdf","label":"IPSJ-Z81-1S-05.pdf"},"date":[{"dateType":"Available","dateValue":"2019-05-28"}],"format":"application/pdf","filename":"IPSJ-Z81-1S-05.pdf","filesize":[{"value":"1.7 MB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"16d6729b-c6e9-414b-b986-66fcbaa0eca8","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2019 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"小田桐, 海翔"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"彌冨, 仁"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"鍵和田, 聡"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"宇賀, 博之"}],"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":"我々はこれまで深層学習手法であるConvolutional Neural Networksを用い，キュウリの病害診断において高い識別精度を達成してきた．現在、他の作物の識別器構築にも取り組んでおり、本報告ではトマトに対する病害診断システムについて報告する．トマトの葉は、キュウリとは異なり極めて多くの複葉から構成されることから撮影された画像の多様性が遥かに大きく，また現状のデータセットでは病気ごとに異なる撮影環境で撮影されていることから，病気の特徴より背景に依存して学習が行われ過学習に陥りやすい．本報告では，限られた学習画像から頑健性の高い識別器を構築するため，様々な背景を組み合わせることにより多様性を増加させるquasi background augmentationを提案し，診断精度に与える影響を検証した．","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"242","bibliographic_titles":[{"bibliographic_title":"第81回全国大会講演論文集"}],"bibliographicPageStart":"241","bibliographicIssueDates":{"bibliographicIssueDate":"2019-02-28","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2019"}]},"relation_version_is_last":true,"weko_creator_id":"6748"},"created":"2025-01-19T01:01:20.393534+00:00","updated":"2025-01-19T22:39:29.947499+00:00"}