{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00230029","sets":["6504:11436:11440"]},"path":["11440"],"owner":"44499","recid":"230029","title":["混合余事象分布に基づく未学習推定畳込みニューラルネット"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-02-16"},"_buckets":{"deposit":"c87ab70c-9c47-40e0-8d8d-322dbb54185d"},"_deposit":{"id":"230029","pid":{"type":"depid","value":"230029","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"混合余事象分布に基づく未学習推定畳込みニューラルネット","author_link":["618863","618864","618865"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"混合余事象分布に基づく未学習推定畳込みニューラルネット"}]},"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":"横浜国大"},{"subitem_text_value":"神奈川県立産業技術総合研究所"},{"subitem_text_value":"横浜国大"}]},"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/230029/files/IPSJ-Z85-7S-02.pdf","label":"IPSJ-Z85-7S-02.pdf"},"date":[{"dateType":"Available","dateValue":"2023-11-17"}],"format":"application/pdf","filename":"IPSJ-Z85-7S-02.pdf","filesize":[{"value":"690.4 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"e5c4274c-b9a2-4882-ae2b-5ed6db14888c","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":"三苫, 凌"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"迎田, 隆幸"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"島, 圭介"}],"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，ニューラルネットの分類結果に対する信頼性が重要視され，学習時に想定しない未知クラスのデータの存在を考慮できるオープンセット認識（OSR）が注目されている．我々の研究グループでは少量のデータでも学習可能なOSR手法を提案したが，画像等の高次元なデータに十分対応できていない．本研究では，提案法に畳込み層を追加することで高次元かつ少量の学習データに対応したOSRの実現を試みた．学習時には畳込み層に対して対照学習を用いることで確率モデルによる特徴空間の解釈を可能にし，更に正則化項を追加することで識別領域の制御を試みた．検証実験ではベンチマークデータの分類を行い，提案法の有効性を確認した．","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"470","bibliographic_titles":[{"bibliographic_title":"第85回全国大会講演論文集"}],"bibliographicPageStart":"469","bibliographicIssueDates":{"bibliographicIssueDate":"2023-02-16","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2023"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":230029,"updated":"2025-01-19T11:19:07.302125+00:00","links":{},"created":"2025-01-19T01:29:32.698085+00:00"}