{"created":"2023-06-26T11:00:48.648247+00:00","id":1401,"links":{},"metadata":{"_buckets":{"deposit":"a8ed8634-b2cb-484d-ab49-55766e4b71f6"},"_deposit":{"created_by":29,"id":"1401","owners":[29],"pid":{"revision_id":0,"type":"depid","value":"1401"},"status":"published"},"_oai":{"id":"oai:oist.repo.nii.ac.jp:00001401","sets":["86:203"]},"author_link":["8489","8490"],"item_10003_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2018-10-24","bibliographicIssueDateType":"Issued"},"bibliographicPageEnd":"49","bibliographicPageStart":"48","bibliographic_titles":[{"bibliographic_title":"第 28 回 日本神経回路学会全国大会 講演論文集"},{"bibliographic_title":"The Proceedings of the 28th Annual Conference of the Japanese Neural Network Society","bibliographic_titleLang":"en"}]}]},"item_10003_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"Convolutional recurrent neural networks (ConvRNNs) provide robust spatio-temporal information processing capabilities for contextual video recognition, but require extensive computation that slows down training. Inspired by detrending methods, we propose “adaptive detrending” (AD) for temporal normalization in order to accelerate the training of ConvRNNs, especially of convolutional gated recurrent unit (ConvGRU).","subitem_description_type":"Abstract"}]},"item_10003_publisher_8":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"Japanese Neural Network Society"}]},"item_10003_relation_17":{"attribute_name":"関連サイト","attribute_value_mlt":[{"subitem_relation_type_id":{"subitem_relation_type_id_text":"http://jnns.org/conference/2018/en/program.html","subitem_relation_type_select":"URI"}}]},"item_10003_rights_15":{"attribute_name":"権利","attribute_value_mlt":[{"subitem_rights":"© 2018 Japanese Neural Network Society"}]},"item_10003_version_type_20":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_ab4af688f83e57aa","subitem_version_type":"AM"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Jung, Minju","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Tani, Jun","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2020-04-24"}],"displaytype":"detail","filename":"jnns2018 Minju.pdf","filesize":[{"value":"269.3 kB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"jnns2018 Minju","url":"https://oist.repo.nii.ac.jp/record/1401/files/jnns2018 Minju.pdf"},"version_id":"ab13cc9e-c7c0-4f0e-94c6-1bfeadd24da3"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"conference paper","resourceuri":"http://purl.org/coar/resource_type/c_5794"}]},"item_title":"Adaptive Detrending for Accelerating the Training of Convolutional Recurrent Neural Networks","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Adaptive Detrending for Accelerating the Training of Convolutional Recurrent Neural Networks","subitem_title_language":"en"}]},"item_type_id":"10003","owner":"29","path":["203"],"pubdate":{"attribute_name":"公開日","attribute_value":"2020-04-24"},"publish_date":"2020-04-24","publish_status":"0","recid":"1401","relation_version_is_last":true,"title":["Adaptive Detrending for Accelerating the Training of Convolutional Recurrent Neural Networks"],"weko_creator_id":"29","weko_shared_id":29},"updated":"2023-06-26T11:51:33.157454+00:00"}