{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00236118","sets":["6504:11678:11689"]},"path":["11689"],"owner":"44499","recid":"236118","title":["ハイブリッド深層学習を用いた果実画像からの糖度推定手法におけるデータ入力・モデル構成最適化に向けた検討"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-03-01"},"_buckets":{"deposit":"59344095-cf32-42a2-aa22-d0334aa1e143"},"_deposit":{"id":"236118","pid":{"type":"depid","value":"236118","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"ハイブリッド深層学習を用いた果実画像からの糖度推定手法におけるデータ入力・モデル構成最適化に向けた検討","author_link":["645301","645300"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"ハイブリッド深層学習を用いた果実画像からの糖度推定手法におけるデータ入力・モデル構成最適化に向けた検討"}]},"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":"愛知工大"},{"subitem_text_value":"愛知工大"}]},"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/236118/files/IPSJ-Z86-1T-04.pdf","label":"IPSJ-Z86-1T-04.pdf"},"date":[{"dateType":"Available","dateValue":"2024-07-03"}],"format":"application/pdf","filename":"IPSJ-Z86-1T-04.pdf","filesize":[{"value":"401.0 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"d0b43f69-266c-4434-86e9-1476fc226c42","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":"上野, 延典"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"森本, 正志"}],"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":"近年、食品の安全性や成分などの情報に関する消費者の需要や関心は高まっている。しかし、消費者が個々の食品情報を簡単に入手できるようにはなっていない。そこで本研究では、果物を撮影した画像から簡単においしさの情報を得る手法に関して取り組んでいる。本稿では糖度がおいしさに直結しており、他の果物に比べて購入時の当たり外れが多いとされる桃を研究対象とする。また糖度推定手法として、MLPとCNNを結合したハイブリッド深層学習モデルを提案する。ハイブリッドモデルの層構成およびデータ入力の最適化に向けた比較評価実験を行うことで、その有効性と課題を明らかにした。","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"564","bibliographic_titles":[{"bibliographic_title":"第86回全国大会講演論文集"}],"bibliographicPageStart":"563","bibliographicIssueDates":{"bibliographicIssueDate":"2024-03-01","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2024"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":236118,"updated":"2025-01-19T09:23:18.060684+00:00","links":{},"created":"2025-01-19T01:37:59.666382+00:00"}