{"created":"2023-05-15T12:28:57.559976+00:00","id":22599,"links":{},"metadata":{"_buckets":{"deposit":"fb37c294-d674-46f1-8053-8ca9953d00ba"},"_deposit":{"created_by":10,"id":"22599","owners":[10],"pid":{"revision_id":0,"type":"depid","value":"22599"},"status":"published"},"_oai":{"id":"oai:kansai-u.repo.nii.ac.jp:00022599","sets":["363:3037"]},"author_link":["46284","50988"],"item_10009_alternative_title_1":{"attribute_name":"その他（別言語等）のタイトル","attribute_value_mlt":[{"subitem_alternative_title":"Handwritten Text Recognition for Historical Documents through Deep Learning : Towards More Efficient Corpus Development Process"}]},"item_10009_date_11":{"attribute_name":"出版年月日","attribute_value_mlt":[{"subitem_date_issued_datetime":"2022-03-31","subitem_date_issued_type":"Issued"}]},"item_10009_description_5":{"attribute_name":"概要","attribute_value_mlt":[{"subitem_description":"This paper discusses the differences and suitable uses of three handwritten text recognition (HTR) programs developed in Europe: Transkribus, eScriptorium/Kraken, and OCR4all. It commences with an overview of deep learning, HTR, and OCR (optical character recognition) before progressing to review the three programs of interest from the perspectives of history, developer, accuracy rate, layout recognition (including writing orientation), user experience, and cost. All three programs use deep-learning machine-learning technologies. They have also all been proven to reach accuracy rates of close to one hundred percent when appropriately trained depending on the quality of the images of handwritten text, training data, and validation data. Second, the user experience is very important; Transkribus has the simplest installation procedure and graphical user interface, while OCR4all and eScriptorium require users to have expert computer skills. Third, in terms of cost, users of Transkribus are required to purchase credits to access the system and use HTR models to recognize a new text, while eScriptorium and OCR4all do not rely on credit purchase. Finally, we conclude this paper with an overview of suitable cases for each program.","subitem_description_type":"Other"}]},"item_10009_end_page_10":{"attribute_name":"終了ページ","attribute_value_mlt":[{"subitem_end_page":"336"}]},"item_10009_full_name_24":{"attribute_name":"著者別名","attribute_value_mlt":[{"nameIdentifiers":[{"nameIdentifier":"50988","nameIdentifierScheme":"WEKO"}],"names":[{"name":"Miyagawa, So"}]}]},"item_10009_identifier_registration":{"attribute_name":"ID登録","attribute_value_mlt":[{"subitem_identifier_reg_text":"10.32286/00026614","subitem_identifier_reg_type":"JaLC"}]},"item_10009_publisher_8":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"関西大学アジア・オープン・リサーチセンター"}]},"item_10009_record_name_7":{"attribute_name":"図書名","attribute_value_mlt":[{"subitem_record_name":"KU-ORCASが開くデジタル化時代の東アジア文化研究 : オープン・プラットフォームで浮かび上がる、新たな東アジアの姿"}]},"item_10009_start_page_9":{"attribute_name":"開始ページ","attribute_value_mlt":[{"subitem_start_page":"323"}]},"item_10009_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":"宮川, 創"}],"nameIdentifiers":[{},{}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2022-05-12"}],"displaytype":"detail","filename":"KU-0440-20220331-29.pdf","filesize":[{"value":"3.0 MB"}],"format":"application/pdf","licensetype":"license_9","mimetype":"application/pdf","url":{"label":"KU-0440-20220331-29.pdf","url":"https://kansai-u.repo.nii.ac.jp/record/22599/files/KU-0440-20220331-29.pdf"},"version_id":"4fe40862-6902-4414-a8ca-766a5a78b9de"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"HTR(手書きテキスト認識)","subitem_subject_scheme":"Other"},{"subitem_subject":"OCR(光学文字認識)","subitem_subject_scheme":"Other"},{"subitem_subject":"自動翻刻","subitem_subject_scheme":"Other"},{"subitem_subject":"コーパス開発","subitem_subject_scheme":"Other"},{"subitem_subject":"ディープラーニング(深層学習)","subitem_subject_scheme":"Other"},{"subitem_subject":"関西大学","subitem_subject_scheme":"Other"},{"subitem_subject":"Kansai University","subitem_subject_scheme":"Other"}]},"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":"book","resourceuri":"http://purl.org/coar/resource_type/c_2f33"}]},"item_title":"ディープラーニングを用いた歴史的手書き文献の自動翻刻 : コーパス開発の効率化に向けて","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"ディープラーニングを用いた歴史的手書き文献の自動翻刻 : コーパス開発の効率化に向けて"}]},"item_type_id":"10009","owner":"10","path":["3037"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-05-12"},"publish_date":"2022-05-12","publish_status":"0","recid":"22599","relation_version_is_last":true,"title":["ディープラーニングを用いた歴史的手書き文献の自動翻刻 : コーパス開発の効率化に向けて"],"weko_creator_id":"10","weko_shared_id":-1},"updated":"2023-05-15T17:23:52.737384+00:00"}