{"created":"2025-01-19T01:17:20.333616+00:00","updated":"2025-01-19T15:43:17.071238+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00216824","sets":["1164:3980:10839:10840"]},"path":["10840"],"owner":"44499","recid":"216824","title":["車載画像送信量を削減するためのfalse negative抑圧CNNモデルを活用した画像判別手法"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-03-01"},"_buckets":{"deposit":"5b4602c0-deda-4fe1-9d3a-cbd1a5980b62"},"_deposit":{"id":"216824","pid":{"type":"depid","value":"216824","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"車載画像送信量を削減するためのfalse negative抑圧CNNモデルを活用した画像判別手法","author_link":["560511","560510","560512","560513"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"車載画像送信量を削減するためのfalse negative抑圧CNNモデルを活用した画像判別手法"},{"subitem_title":"An Image Discrimination Method Utilizing CNN Model to Suppress False Negative in order to Reduce the Network Traffic of In-Vehicle Cameras","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2022-03-01","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"慶應義塾大学総合政策学部"},{"subitem_text_value":"慶應義塾大学環境情報学部"},{"subitem_text_value":"慶應義塾大学政策・メディア研究科"},{"subitem_text_value":"慶應義塾大学"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Faculty of Policy Management, Keio University","subitem_text_language":"en"},{"subitem_text_value":"Faculty of Environment and Information Studies, Keio University","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Media and Governance, Keio University","subitem_text_language":"en"},{"subitem_text_value":"Keio 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/216824/files/IPSJ-ITS22088002.pdf","label":"IPSJ-ITS22088002.pdf"},"date":[{"dateType":"Available","dateValue":"2024-03-01"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-ITS22088002.pdf","filesize":[{"value":"1.7 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":"37"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"e086b474-5484-46ce-adef-7631c742db6b","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2022 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"石原, 匠"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"赤間, 滉星"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"佐藤, 雅明"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"村井, 純"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11515904","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":"2188-8965","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"近年，画像認識による物体検知サービスが多数展開されており，特にモビリティ分野では衝突被害軽減ブレーキや自動運転分野などで利用されている．将来的には，こうした画像は車両単体のみでなく，遠隔地からの走行監視や指示，複数車両の情報からの交通状況把握への利用が期待されている．全ての車両から常に画像情報を送信するのはネットワーク負荷が大きく，車両側で送信の有無や優先度を判別するシステムが必要となる．本研究では，車両側で画像の有用性や重要度を評価し，必要と判断した時のみ遠隔地に送信する手法を提案する．また，ユースケースとして車両のカメラから障害物画像を集約するシステムを挙げ，「誤検知は許容しても検知漏れ (false negative) は許容しない」ポリシーで送信の判断をおこなう CNN モデルを実装し，手法の有用性に関する評価を行った．その結果，ポリシーに基づいた車両側での判断によって必要な画像を欠損することなく通信量の削減が可能であることを示した．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"7","bibliographic_titles":[{"bibliographic_title":"研究報告高度交通システムとスマートコミュニティ（ITS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2022-03-01","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"2","bibliographicVolumeNumber":"2022-ITS-88"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":216824,"links":{}}