{"created":"2020-09-01T14:22:33.675982+00:00","id":4232,"links":{},"metadata":{"_buckets":{"deposit":"e53be892-8df3-40b8-8854-4c2b96af626a"},"_deposit":{"id":"4232","owners":[],"pid":{"revision_id":0,"type":"recid","value":"4232"},"status":"published"},"_oai":{"id":"oai:meral.edu.mm:recid/4232","sets":["1582963302567:1597824273898"]},"communities":["ucsy"],"item_1583103067471":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"Feature Extraction and Recognition of Handwritten English Character Using Artificial Neural Network","subitem_1551255648112":"en"}]},"item_1583103085720":{"attribute_name":"Description","attribute_value_mlt":[{"interim":"This paper presents the development of EnglishHandwritten character recognition system, whichuses local and global features of English charactersby applying the concept of feature feeding. After eachcharacter is extracted, the features are fed to therecognition engine. A well-known Multi-layerFeedforward neural network with backpropagationlearning algorithm is chosen for its fast processingtime and its good performance for patternrecognition problems. Backpropagation Learningalgorithm is prefered for training of neural network.Training set occurs of various English characterscollected from different people. The characters arepresented directly to the network and correctly sizedin pre-processing. In applying with free-handEnglish single characters, the average recognitionrate of 91% has been achieved this confirms that theproposed approach is suitable for the development ofEnglish handwritten character recognition system.Recognition percentage of the system is higher thanacceptable level. Input data, network parameters andtraining period affect the result."}]},"item_1583103108160":{"attribute_name":"Keywords","attribute_value":[]},"item_1583103120197":{"attribute_name":"Files","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2019-08-06"}],"displaytype":"preview","filename":"59032.pdf","filesize":[{"value":"77 Kb"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"url":"https://meral.edu.mm/record/4232/files/59032.pdf"},"version_id":"7387e660-582e-407e-8c68-716c4f75634a"}]},"item_1583103131163":{"attribute_name":"Journal articles","attribute_value_mlt":[{"subitem_issue":"","subitem_journal_title":"Fourth Local Conference on Parallel and Soft Computing","subitem_pages":"","subitem_volume":""}]},"item_1583103147082":{"attribute_name":"Conference papers","attribute_value_mlt":[{"subitem_acronym":"","subitem_c_date":"","subitem_conference_title":"","subitem_part":"","subitem_place":"","subitem_session":"","subitem_website":""}]},"item_1583103211336":{"attribute_name":"Books/reports/chapters","attribute_value_mlt":[{"subitem_book_title":"","subitem_isbn":"","subitem_pages":"","subitem_place":"","subitem_publisher":""}]},"item_1583103233624":{"attribute_name":"Thesis/dissertations","attribute_value_mlt":[{"subitem_awarding_university":"","subitem_supervisor(s)":[{"subitem_supervisor":""}]}]},"item_1583105942107":{"attribute_name":"Authors","attribute_value_mlt":[{"subitem_authors":[{"subitem_authors_fullname":"Min, Ei Phyo"},{"subitem_authors_fullname":"Thein, Yadana"}]}]},"item_1583108359239":{"attribute_name":"Upload type","attribute_value_mlt":[{"interim":"Publication"}]},"item_1583108428133":{"attribute_name":"Publication type","attribute_value_mlt":[{"interim":"Article"}]},"item_1583159729339":{"attribute_name":"Publication date","attribute_value":"2009-12-30"},"item_1583159847033":{"attribute_name":"Identifier","attribute_value":"http://onlineresource.ucsy.edu.mm/handle/123456789/1923"},"item_title":"Feature Extraction and Recognition of Handwritten English Character Using Artificial Neural Network","item_type_id":"21","owner":"1","path":["1597824273898"],"publish_date":"2019-08-06","publish_status":"0","recid":"4232","relation_version_is_last":true,"title":["Feature Extraction and Recognition of Handwritten English Character Using Artificial Neural Network"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2021-12-13T01:30:44.726977+00:00"}