{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00235990","sets":["6504:11678:11689"]},"path":["11689"],"owner":"44499","recid":"235990","title":["歩行軌跡の予測における特徴別学習の有効性について"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-03-01"},"_buckets":{"deposit":"92da42db-919c-4b68-89c6-311353bab3ee"},"_deposit":{"id":"235990","pid":{"type":"depid","value":"235990","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"歩行軌跡の予測における特徴別学習の有効性について","author_link":["644931","644930"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"歩行軌跡の予測における特徴別学習の有効性について"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"人工知能と認知科学","subitem_subject_scheme":"Other"}]},"item_type_id":"22","publish_date":"2024-03-01","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":"法大"},{"subitem_text_value":"法大"}]},"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/235990/files/IPSJ-Z86-4Q-04.pdf","label":"IPSJ-Z86-4Q-04.pdf"},"date":[{"dateType":"Available","dateValue":"2024-07-03"}],"format":"application/pdf","filename":"IPSJ-Z86-4Q-04.pdf","filesize":[{"value":"270.8 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"427268e4-db52-40de-b18e-b3b16d724a06","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"小林, 光乃佑"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"藤田, 悟"}],"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":"歩行軌跡の予測は、過去の歩行軌跡や周囲の歩行者の存在など、さまざまな要因を考慮する必要がある。既存研究では、大量の歩行データをLSTMなどの1つの共通のディープラーニングモデルに学習させることで、歩行者の歩行特徴を抽出し、予測を行っている。しかし、これは、歩行特徴が周囲と大きく異なる歩行者の特徴が抽出されない平均的なモデルとなってしまうおそれがある。そこで、本論文では歩行者を歩行特徴、例えば、歩行速度でクラス分けを行い、クラス別に学習・予測をすることで、あらゆる歩行者の特徴を抽出して、より高い予測精度を示すことを確認する。","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"294","bibliographic_titles":[{"bibliographic_title":"第86回全国大会講演論文集"}],"bibliographicPageStart":"293","bibliographicIssueDates":{"bibliographicIssueDate":"2024-03-01","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2024"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":235990,"updated":"2025-01-19T09:26:18.648481+00:00","links":{},"created":"2025-01-19T01:37:47.990208+00:00"}