{"created":"2025-01-19T01:30:05.142382+00:00","updated":"2025-01-19T11:10:39.893596+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00230366","sets":["6504:11436:11441"]},"path":["11441"],"owner":"44499","recid":"230366","title":["車載カメラ映像と周辺の交通量データを用いた交通量予測手法の検討"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-02-16"},"_buckets":{"deposit":"9236af27-bb30-4d98-8c44-84bfc78d952a"},"_deposit":{"id":"230366","pid":{"type":"depid","value":"230366","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"車載カメラ映像と周辺の交通量データを用いた交通量予測手法の検討","author_link":["620559","620558","620557","620560"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"車載カメラ映像と周辺の交通量データを用いた交通量予測手法の検討"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"ネットワーク","subitem_subject_scheme":"Other"}]},"item_type_id":"22","publish_date":"2023-02-16","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_22_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"東大"},{"subitem_text_value":"東大"},{"subitem_text_value":"東大"},{"subitem_text_value":"東大"}]},"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/230366/files/IPSJ-Z85-2ZA-06.pdf","label":"IPSJ-Z85-2ZA-06.pdf"},"date":[{"dateType":"Available","dateValue":"2023-11-17"}],"format":"application/pdf","filename":"IPSJ-Z85-2ZA-06.pdf","filesize":[{"value":"664.8 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"73143a6b-7310-4cde-baea-632620465e83","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2023 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"宇都, 翼"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"谷合, 廣紀"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"入江, 英嗣"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"坂井, 修一"}],"nameIdentifiers":[{}]}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_5794","resourcetype":"conference paper"}]},"item_22_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00349328","subitem_source_identifier_type":"NCID"}]},"item_22_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"交通量は交通状況を把握するのに重要な指標であり，全国に交通量計測機器が設置されている．一般に各計測地点の交通量には時間的・空間的な相関があり，深層学習によってその相関関係を利用して高精度に交通量を予測する手法が研究されているが，計測機器のない地点の交通量を予測する場合，その手法をそのまま利用できない．そこで，プローブデータや周囲の計測地点から計測機器のない地点の交通量を予測することが求められている．本研究では，過去の交通量データがない地点の交通量を，周囲の計測地点の時間的・空間的な関係性を考慮して予測する手法を提案する．また，車載カメラ映像からの予測地点の情報を活用することを提案し検証した．","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"200","bibliographic_titles":[{"bibliographic_title":"第85回全国大会講演論文集"}],"bibliographicPageStart":"199","bibliographicIssueDates":{"bibliographicIssueDate":"2023-02-16","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2023"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":230366,"links":{}}