{"updated":"2025-01-19T22:19:06.512665+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00197515","sets":["1164:1579:9681:9819"]},"path":["9819"],"owner":"44499","recid":"197515","title":["エッジ環境におけるニューラルネットワーク学習軽量化手法の検討"],"pubdate":{"attribute_name":"公開日","attribute_value":"2019-06-04"},"_buckets":{"deposit":"680da6d2-60fe-4085-ac5a-e13b5cf817b7"},"_deposit":{"id":"197515","pid":{"type":"depid","value":"197515","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"エッジ環境におけるニューラルネットワーク学習軽量化手法の検討","author_link":["473918","473920","473921","473919","473922","473924","473923","473925"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"エッジ環境におけるニューラルネットワーク学習軽量化手法の検討"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"ニューラルネットワーク","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2019-06-04","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"北海道大学"},{"subitem_text_value":"北海道大学"},{"subitem_text_value":"東京工業大学"},{"subitem_text_value":"科学技術振興機構さきがけ"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Hokkaido University","subitem_text_language":"en"},{"subitem_text_value":"Hokkaido University","subitem_text_language":"en"},{"subitem_text_value":"Tokyo Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"JST PRESTO","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/197515/files/IPSJ-ARC19236009.pdf","label":"IPSJ-ARC19236009.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-ARC19236009.pdf","filesize":[{"value":"545.2 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"16"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"b090c89f-c814-4ed3-b755-84696cca0860","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":"廣瀬, 一俊"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"浅井, 哲也"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"本村, 真人"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"高前田, 伸也"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Kazutoshi, Hirose","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Tetsuya, Asai","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Masato, Motomura","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Shinya, Takamaeda","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10096105","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":"2188-8574","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"IoT 端末における情報処理の高度化に向け，ニューラルネットワークの推論だけではなく学習も行うことが期待されている．しかし，エッジ環境では演算資源や電力に制約があるため，演算コストやメモリ使用量の大きい誤差逆伝播法による大規模な学習を行うのは現実的ではない．本研究では，エッジ環境での誤差逆伝播法に頼らない，メモリ使用量 ・演算量ともに軽量な学習手法の検討を行った．CIFAR-100 を用いた評価の結果，誤差逆伝播法で最終層のみのファインチューニングを行う場合に比べて，一定のメモリ量増加に抑えながらより高い認識精度で学習可能であることがわかった．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告システム・アーキテクチャ（ARC）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2019-06-04","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"9","bibliographicVolumeNumber":"2019-ARC-236"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T01:01:58.169129+00:00","id":197515,"links":{}}