{"links":{},"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00195114","sets":["1164:1579:9681:9756"]},"path":["9756"],"owner":"44499","recid":"195114","title":["車載応用向けDNNモデル軽量化の検討"],"pubdate":{"attribute_name":"公開日","attribute_value":"2019-03-10"},"_buckets":{"deposit":"c1a3a3bf-022c-43d6-96ca-054811774fa3"},"_deposit":{"id":"195114","pid":{"type":"depid","value":"195114","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"車載応用向けDNNモデル軽量化の検討","author_link":["463702","463705","463706","463709","463700","463707","463701","463703","463704","463708"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"車載応用向けDNNモデル軽量化の検討"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"機械学習","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2019-03-10","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"北海道大学大学院情報科学研究科"},{"subitem_text_value":"北海道大学大学院情報科学研究科"},{"subitem_text_value":"NECソリューションイノベータ株式会社"},{"subitem_text_value":"NECソリューションイノベータ株式会社"},{"subitem_text_value":"NECソリューションイノベータ株式会社"},{"subitem_text_value":"NECソリューションイノベータ株式会社"},{"subitem_text_value":"北海道大学大学院情報科学研究科"},{"subitem_text_value":"北海道大学大学院情報科学研究科"}]},"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/195114/files/IPSJ-ARC19235034.pdf","label":"IPSJ-ARC19235034.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-ARC19235034.pdf","filesize":[{"value":"627.0 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"16"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"ef293414-477e-4d86-ac27-a721d7690313","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":"平山, 侑樹"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"廣獺, 一俊"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"早川, 剛"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"気屋村, 純一"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"深谷, 安利"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"栗田, 裕二"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"安藤, 洸太"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"植吉, 晃大"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"高前田, 伸也"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"本村, 真人"}],"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":"ハードウェア実装に向けた畳み込みニューラルネットワークの量子化手法について検討した.パラメータ間での量子化の度合いの関係について議論したものは少なく、高精度を保ったまま、かつ計算量を減らしたい.そこで Residual Network [1] を対象とし、活性、重み、バッチ正規化、畳み込み演算の出力それぞれに対し、個別のビット幅、スケールを設定することにより、一般にスケールの異なる値の効率的な量子化手法について提案する.独自に用意した歩行者検出のデータセットを用いてその性能を評価するとともに、CIFAR-10 による評価を行った.歩行者検出のデータセットにおいて浮動小数点での演算とほぼ変わらない精度を実現できることを示した.","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":"2019-03-10","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"34","bibliographicVolumeNumber":"2019-ARC-235"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"updated":"2025-01-19T23:12:48.753515+00:00","created":"2025-01-19T01:00:07.772811+00:00","id":195114}