{"created":"2025-01-19T01:00:55.083667+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00196213","sets":["6504:9795:9813"]},"path":["9813"],"owner":"6748","recid":"196213","title":["ノイズを用いた深層学習における学習モデルの解釈性に関する一考察"],"pubdate":{"attribute_name":"公開日","attribute_value":"2019-02-28"},"_buckets":{"deposit":"b74566d8-c86b-4954-91dc-b6170aa56e85"},"_deposit":{"id":"196213","pid":{"type":"depid","value":"196213","revision_id":0},"owners":[6748],"status":"published","created_by":6748},"item_title":"ノイズを用いた深層学習における学習モデルの解釈性に関する一考察","author_link":["469350","469351","469349"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"ノイズを用いた深層学習における学習モデルの解釈性に関する一考察"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"データとウェブ","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":"工学院大"},{"subitem_text_value":"工学院大"},{"subitem_text_value":"工学院大"}]},"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/196213/files/IPSJ-Z81-4Q-07.pdf","label":"IPSJ-Z81-4Q-07.pdf"},"date":[{"dateType":"Available","dateValue":"2019-05-27"}],"format":"application/pdf","filename":"IPSJ-Z81-4Q-07.pdf","filesize":[{"value":"713.0 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"79e3f17c-9904-4833-9685-2d08e160befb","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":"中村, 鴻介"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"佐藤, 悠祐"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"山口, 実靖"}],"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":"深層学習は自然言語処理・画像認識などの問題に対して従来の機械学習手法よりも高性能な推論が可能である．しかしながら，深層学習モデルは，推論の判断根拠がわからず，判断された過程が重要な場合に根拠が提示できないという問題点がある．本研究では深層学習の判断根拠を示すことに取り組む．本稿では，判断根拠を示すためのアプローチとして，モデルにある入力を加えたときの勾配の大きさを可視化する手法に着目し，判断根拠の提示について考察を行う．","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"446","bibliographic_titles":[{"bibliographic_title":"第81回全国大会講演論文集"}],"bibliographicPageStart":"445","bibliographicIssueDates":{"bibliographicIssueDate":"2019-02-28","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2019"}]},"relation_version_is_last":true,"weko_creator_id":"6748"},"id":196213,"updated":"2025-01-19T22:49:32.497364+00:00","links":{}}