{"created":"2023-06-19T10:35:10.244542+00:00","id":1120,"links":{},"metadata":{"_buckets":{"deposit":"578dfd8a-cce3-4e4a-bb2a-f1940418ee8d"},"_deposit":{"created_by":14,"id":"1120","owners":[14],"pid":{"revision_id":0,"type":"depid","value":"1120"},"status":"published"},"_oai":{"id":"oai:ous.repo.nii.ac.jp:00001120","sets":["296:314:328"]},"author_link":["11463","11464","11465"],"item_1_biblio_info_14":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"1995-03-31","bibliographicIssueDateType":"Issued"},"bibliographicPageEnd":"327","bibliographicPageStart":"319","bibliographicVolumeNumber":"30","bibliographic_titles":[{"bibliographic_title":"岡山理科大学紀要. A, 自然科学","bibliographic_titleLang":"ja"},{"bibliographic_title":"Bulletin of Okayama University of Science. A, Natural Sciences","bibliographic_titleLang":"en"}]}]},"item_1_creator_6":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"大倉, 充","creatorNameLang":"ja"},{"creatorName":"オオクラ, ミツル","creatorNameLang":"ja-Kana"},{"creatorName":"Ohkura, Mitsuru","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"塩野, 充","creatorNameLang":"ja"},{"creatorName":"シオノ, ミツル","creatorNameLang":"ja-Kana"},{"creatorName":"Shiono, Mitsuru","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"橋本, 禮治","creatorNameLang":"ja"},{"creatorName":"ハシモト, レイジ","creatorNameLang":"ja-Kana"},{"creatorName":"Hashimoto, Reiji","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_1_description_1":{"attribute_name":"ページ属性","attribute_value_mlt":[{"subitem_description":"P(論文)","subitem_description_type":"Other"}]},"item_1_description_12":{"attribute_name":"抄録(英)","attribute_value_mlt":[{"subitem_description":"Handwritten HIRAGANA characters are classified according to whether they have DAKUTEN (or HAN-DAKUTEN) or not by the 3-layer neural networks. The input data to the networks is 25-dimensional local mesh-feature extracted from an original character pattern. The numbers of units of three layers are 25 (input-layer), 25 (hidden-layer) and 2 (output-layer). The numbers of training and unknown samples used in a classification experiment are 6900 and 5000,respectively. The average classification rate of 94(%) for the unknown samples is obtained.","subitem_description_language":"en","subitem_description_type":"Other"}]},"item_1_source_id_13":{"attribute_name":"雑誌書誌ID","attribute_value_mlt":[{"subitem_source_identifier":"AN00033244","subitem_source_identifier_type":"NCID"}]},"item_1_text_10":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_language":"en","subitem_text_value":"Department of Information and Computer Engineering, Okayama University of Science"},{"subitem_text_language":"en","subitem_text_value":"Department of Information and Computer Engineering, Okayama University of Science"},{"subitem_text_language":"en","subitem_text_value":"Department of Electronic Engineering, Okayama University of Science"}]},"item_1_text_9":{"attribute_name":"著者所属(日)","attribute_value_mlt":[{"subitem_text_language":"ja","subitem_text_value":"岡山理科大学工学部情報工学科"},{"subitem_text_language":"ja","subitem_text_value":"岡山理科大学工学部情報工学科"},{"subitem_text_language":"ja","subitem_text_value":"岡山理科大学工学部電子工学科"}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"1995-03-31"}],"displaytype":"detail","filename":"KJ00000063629.pdf","filesize":[{"value":"418.4 kB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"url":"https://ous.repo.nii.ac.jp/record/1120/files/KJ00000063629.pdf"},"version_id":"4a5342aa-4459-478c-8e00-75f237f8ed64"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"departmental bulletin paper","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"ニューラルネットワークを用いた濁点,半濁点の有無による手書き平仮名の分類","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"ニューラルネットワークを用いた濁点,半濁点の有無による手書き平仮名の分類","subitem_title_language":"ja"},{"subitem_title":"A Classification of Handwritten HIRAGANA Characters by 3-Layer Neural Networks","subitem_title_language":"en"},{"subitem_title":"ニューラル ネットワーク オ モチイタ ダクテン ハンダクテン ノ ウム ニヨル テガキ ヒラガナ ノ ブンルイ","subitem_title_language":"ja-Kana"}]},"item_type_id":"1","owner":"14","path":["328"],"pubdate":{"attribute_name":"PubDate","attribute_value":"1995-03-31"},"publish_date":"1995-03-31","publish_status":"0","recid":"1120","relation_version_is_last":true,"title":["ニューラルネットワークを用いた濁点,半濁点の有無による手書き平仮名の分類"],"weko_creator_id":"14","weko_shared_id":-1},"updated":"2023-09-28T04:53:30.135807+00:00"}