{"created":"2023-05-15T10:01:13.728717+00:00","id":5749,"links":{},"metadata":{"_buckets":{"deposit":"b1032bbb-c419-4dfe-818a-6a6f9507c20a"},"_deposit":{"created_by":5,"id":"5749","owner":"5","owners":[5],"pid":{"revision_id":0,"type":"depid","value":"5749"},"status":"published"},"_oai":{"id":"oai:miyazaki-u.repo.nii.ac.jp:00005749","sets":["71","71:35"]},"author_link":["30984","30985"],"item_10003_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2018-09","bibliographicIssueDateType":"Issued"},"bibliographicPageEnd":"60","bibliographicPageStart":"57","bibliographic_titles":[{"bibliographic_title":"International Conference on Science, Technology & Education (ICSTE 2018)","bibliographic_titleLang":"en"}]}]},"item_10003_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"Study on hand pause rally system has been taking place since 2012 in our laboratory. In this study, a method identifying the posture of a human hands has been developed. The conventional method has several problems. One of them is that accuracy does not readily rise. Therefore, it is necessary for us to build a method of identifying the posture by machine learning using a convolution neural network (CNN) which is an alternative method to the conventional discrimination method. As a result of the verification, the accuracy of the identification was about 40% overall in spite of a small learning data. Therefore, we processed the image data and artificially increased the amount of images. As a result of increasing the learning data and measuring it, the accuracy reached 54%. Currently we are studying ways to improve accuracy other than increasing the amount of images.","subitem_description_language":"en","subitem_description_type":"Abstract"}]},"item_10003_version_type_20":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_970fb48d4fbd8a85","subitem_version_type":"VoR"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Hirakawa, Motoya","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"30984","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Suganuma, Akira","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"30985","nameIdentifierScheme":"WEKO"}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2020-06-21"}],"displaytype":"detail","filename":"p57_icste2018.pdf","filesize":[{"value":"576.7 kB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"本文","url":"https://miyazaki-u.repo.nii.ac.jp/record/5749/files/p57_icste2018.pdf"},"version_id":"5028e6b4-f6dd-465e-8ad9-a3af8ac200b1"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"hand pose, convolution neural network, machine learning","subitem_subject_language":"en","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"conference paper","resourceuri":"http://purl.org/coar/resource_type/c_5794"}]},"item_title":"Pose Estimation of Player's Hand with CNN for the Hand Pose Rally System","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Pose Estimation of Player's Hand with CNN for the Hand Pose Rally System","subitem_title_language":"en"}]},"item_type_id":"10003","owner":"5","path":["71","35"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2020-06-21"},"publish_date":"2020-06-21","publish_status":"0","recid":"5749","relation_version_is_last":true,"title":["Pose Estimation of Player's Hand with CNN for the Hand Pose Rally System"],"weko_creator_id":"5","weko_shared_id":-1},"updated":"2024-10-03T06:24:14.487598+00:00"}