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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":"2188-8582","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"競技スポーツにおいて映像分析が重要視されており，様々な映像分析に関する研究が行われている．バドミントン競技では，ショット情報がパフォーマンス分析のための重要な基礎データであるが，ショット情報の検出はソフトウェアを用いた手動入力が一般的である．そこで本研究では，バドミントンの競技映像からショット情報を自動検出することを目的とする．選手の移動軌跡を解析し，深層学習分類を用いてヒットタイミングを予測する．さらにコートを 9 分割し，ヒットタイミングにおける選手の位置する領域を打点領域として検出する．以上より，提案手法の有効性を確認する．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告オーディオビジュアル複合情報処理（AVM）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2022-11-17","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"13","bibliographicVolumeNumber":"2022-AVM-119"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T01:22:20.637414+00:00","id":222386,"links":{}}