{"id":197619,"created":"2025-01-19T01:02:03.239316+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00197619","sets":["1164:5352:9740:9828"]},"path":["9828"],"owner":"44499","recid":"197619","title":["CNN推論のFPGA実装における小型高速化の報告"],"pubdate":{"attribute_name":"公開日","attribute_value":"2019-06-10"},"_buckets":{"deposit":"aa07e87a-7751-4914-b141-60bb94545445"},"_deposit":{"id":"197619","pid":{"type":"depid","value":"197619","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"CNN推論のFPGA実装における小型高速化の報告","author_link":["474499","474500","474501","474502"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"CNN推論のFPGA実装における小型高速化の報告"},{"subitem_title":"Embedded AI Implementation","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":"三菱電機マイコン機器ソフトウエア(株)"},{"subitem_text_value":"愛媛大学大学院理工学研究科"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Mitsubishi Electric Micro-Computer Application Software Co.,Ltd.","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Ehime 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/197619/files/IPSJ-BIO19058020.pdf","label":"IPSJ-BIO19058020.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-BIO19058020.pdf","filesize":[{"value":"912.8 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"41"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"b4860caf-b412-433a-a237-abbc62bd8c09","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":"白石, 忠明"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"木下, 浩二"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Tadaaki, Shiraishi","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Koji, Kinoshita","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA12055912","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":"2188-8590","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"エッジ端末で CNN を構築して画像認識などの推論処理を実現するには，処理速度や認識精度を維持しつつ，消費電力を抑制し低価格化を実現することが重要な課題となる．今回，CNN の軽量化を実現し FPGA に実装し，組込み系 GPUとの比較実験を行なったので，その結果を報告する．手書き数字を認識する小規模な CNN を各デバイスに実装して比較したところ，価格，消費電力，処理速度の点で FPGA 実装が良好であった．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"In order to realize CNN on edge terminals and realize inference processing such as image recognition, it is important to reduce power consumption and realize price reduction while maintaining processing speed and recognition accuracy. In this paper, we realized the weight reduction of CNN, implemented it in FPGA, and compared it with embedded system GPU, and report the result. When small-scale CNNs that recognize handwritten numbers were implemented on each device and compared, FPGA implementation was good in terms of price, power consumption, and processing speed.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告バイオ情報学（BIO）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2019-06-10","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"20","bibliographicVolumeNumber":"2019-BIO-58"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"updated":"2025-01-19T22:16:55.213566+00:00","links":{}}