{"id":197658,"updated":"2025-01-19T22:15:50.118673+00:00","links":{},"created":"2025-01-19T01:02:05.606113+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00197658","sets":["1164:2735:9724:9827"]},"path":["9827"],"owner":"44499","recid":"197658","title":["ベイズ的深層学習を用いた画像テキスト検索における信頼性評価"],"pubdate":{"attribute_name":"公開日","attribute_value":"2019-06-10"},"_buckets":{"deposit":"309d984c-d682-4fbe-940c-059603166e78"},"_deposit":{"id":"197658","pid":{"type":"depid","value":"197658","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"ベイズ的深層学習を用いた画像テキスト検索における信頼性評価","author_link":["474702","474703","474705","474704","474706","474707"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"ベイズ的深層学習を用いた画像テキスト検索における信頼性評価"},{"subitem_title":"Reliability Assessment by Bayesian Deep Learning for Image-Caption Retrieval Task","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2019-06-10","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"神戸大学大学院システム情報学研究科"},{"subitem_text_value":"神戸大学大学院システム情報学研究科"},{"subitem_text_value":"神戸大学大学院システム情報学研究科"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of System Informatics, Kobe University","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of System Informatics, Kobe University","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of System Informatics, Kobe University","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"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/197658/files/IPSJ-MPS19123001.pdf","label":"IPSJ-MPS19123001.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-MPS19123001.pdf","filesize":[{"value":"1.8 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"17"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"13d92149-2fa7-4cc4-b463-f208238f9838","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2019 by the Institute of Electronics, Information and Communication Engineers This SIG report is only available to those in membership of the SIG."}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"濱, 健太"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"松原, 崇"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"上原, 邦昭"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Kenta, Hama","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takashi, Matsubara","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Kuniaki, Uehara","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10505667","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8833","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"深層ニューラルネットワークを含む，多くの機械学習アルゴリズムで出力結果の信頼性をいかにして評価するかは大きな課題である．分類問題，回帰問題においては，ベイシアンニュートラルネットワークの出力の不確実性によって信頼性を評価する方法が提案されている．しかし，画像テキスト検索は分類や回帰とは異なるタスクであり，信頼性の評価方法を検討する必要がある．本研究では画像テキスト検索を分類問題としての解釈 (事後分布の不確実性)，回帰問題としての解釈 (埋め込み点の不確実性) により二つの不確実性を定義した．その結果，二つの不確実性でモデル平均による検索精度の向上が見られた．また，事後分布の分散が大きいデータをクエリーから除くことで，大幅な精度改善が見られたことから，分類問題としての不確実性が信頼性の評価に適していることを示した．この傾向は異なるデータセット (MSCOCO，Flickr30k)，異なる手法　(dropout，batch normalization)，異なる損失関数で一貫して見られた．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Following the development of black-box machine learning algorithms, the practical demand of the reliability assessment is rapidly rising. Recent progress in Bayesian deep learning has enabled us to quantify the uncertainty of its output, potentially providing a reliability measure. While many previous studies have evaluated the uncertainty measures for classification and regression tasks, their approaches are not always applicable to other tasks. This study investigates two sides of image-caption embedding and retrieval systems The embedding task is similar to the regression task, and the model averaging based on the regression improves the retrieval performance. However, its uncertainty measure cannot evaluate the reliability of retrieval appropriately, and the uncertainty measure for the classification task is applicable. This study confirms that this tendency is common among datasets, DNN architectures, and similarity functions.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"8","bibliographic_titles":[{"bibliographic_title":"研究報告数理モデル化と問題解決（MPS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2019-06-10","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2019-MPS-123"}]},"relation_version_is_last":true,"weko_creator_id":"44499"}}