{"created":"2025-01-19T00:21:03.337721+00:00","updated":"2025-01-20T12:54:21.879441+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00145417","sets":["1164:1579:7841:8344"]},"path":["8344"],"owner":"11","recid":"145417","title":["畳み込みニューラルネットワークにおける数値表現と分類精度に関する調査"],"pubdate":{"attribute_name":"公開日","attribute_value":"2015-10-01"},"_buckets":{"deposit":"6d289737-335b-4663-aab7-0ee9df3fabb4"},"_deposit":{"id":"145417","pid":{"type":"depid","value":"145417","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"畳み込みニューラルネットワークにおける数値表現と分類精度に関する調査","author_link":["224110","224111"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"畳み込みニューラルネットワークにおける数値表現と分類精度に関する調査"}]},"item_type_id":"4","publish_date":"2015-10-01","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"東京大学"},{"subitem_text_value":"東京大学"}]},"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/145417/files/IPSJ-ARC15217008.pdf","label":"IPSJ-ARC15217008.pdf"},"date":[{"dateType":"Available","dateValue":"2017-10-01"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-ARC15217008.pdf","filesize":[{"value":"1.0 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"16"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"6aae3974-35d9-49cb-b7d9-891addab084d","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2015 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"成子, 貴洋"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"平木, 敬"}],"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":"畳み込みニューラルネットワーク (Convolutional Neural Network, CNN) は画像認識アプリケーションに適した機械学習モデルである．CNN は，入力画像とそれが属するクラスのラベルからなる訓練データを基に，自身のパラメータを学習する．学習が完了した CNN は画像の分類器として機能する．計算機的側面から CNN を観察すると，CNN は膨大な浮動小数演算と高い並列性を有することが分かる．この高い並列性を活用して分類に要するレイテンシを削減するために，CNN を FPGA によって高速化する研究が行われてきた．FPGA は浮動小数点数の演算器を持たないため，固定小数点数を数値表現に用いるのが適当である．固定小数点数に何ビットを割り当てるかに関して，必要な FPGA リソースと精度はトレードオフの関係にある．入力画像から分類結果を得る feed forward パスの演算に何ビットの固定小数点数が必要であるかは，先行研究で明らかになっている．しかし，学習を含めた CNN の演算に，何ビットの固定小数点数が必要であるかに関しては十分な知見が得られていない．本稿では，固定小数点数のビット数と丸め方法が CNN の分類性能に与える影響について調査する．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"4","bibliographic_titles":[{"bibliographic_title":"研究報告システム・アーキテクチャ（ARC）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2015-10-01","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"8","bibliographicVolumeNumber":"2015-ARC-217"}]},"relation_version_is_last":true,"weko_creator_id":"11"},"id":145417,"links":{}}