Analyze the effectiveness of an algorithm for identifying Polish characters in handwriting based on neural machine learning technologies

An approach is presented that generalize OCR task including polish letters using deep learning technique. The paper extends EMNIST dataset so that two new classes of polish diacritics “Ą” and “Ć” are attached. Using this new dataset and deep learning technique one can analyze sensitives of standard...

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Autores principales:	Dawid Grzelak, Krzysztof Podlaski, Grzegorz Wiatrowski
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Machine learning Deep learning Convolutional neural networks Neural networks National diacritics Image recognition Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/79e05652511b4c94aba610f87645420d
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id	oai:doaj.org-article:79e05652511b4c94aba610f87645420d
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spelling	oai:doaj.org-article:79e05652511b4c94aba610f87645420d2021-11-22T04:19:40ZAnalyze the effectiveness of an algorithm for identifying Polish characters in handwriting based on neural machine learning technologies1319-157810.1016/j.jksuci.2019.08.001https://doaj.org/article/79e05652511b4c94aba610f87645420d2021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S131915781930148Xhttps://doaj.org/toc/1319-1578An approach is presented that generalize OCR task including polish letters using deep learning technique. The paper extends EMNIST dataset so that two new classes of polish diacritics “Ą” and “Ć” are attached. Using this new dataset and deep learning technique one can analyze sensitives of standard as well as presented extended approach with different parameters of convolutional neural network. The analysis of the results shows that the shadows and noises that Polish characters, leave with their hooks leads, can be properly recognized and two similar letters “A” and “Ą” can be distinguished by convolutional neural network. On the other hand a neural network trained on dataset without Polish characters do not treat letters “Ą” and “Ć” properly.Dawid GrzelakKrzysztof PodlaskiGrzegorz WiatrowskiElsevierarticleMachine learningDeep learningConvolutional neural networksNeural networksNational diacriticsImage recognitionElectronic computers. Computer scienceQA75.5-76.95ENJournal of King Saud University: Computer and Information Sciences, Vol 33, Iss 10, Pp 1258-1264 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Machine learning Deep learning Convolutional neural networks Neural networks National diacritics Image recognition Electronic computers. Computer science QA75.5-76.95
spellingShingle	Machine learning Deep learning Convolutional neural networks Neural networks National diacritics Image recognition Electronic computers. Computer science QA75.5-76.95 Dawid Grzelak Krzysztof Podlaski Grzegorz Wiatrowski Analyze the effectiveness of an algorithm for identifying Polish characters in handwriting based on neural machine learning technologies
description	An approach is presented that generalize OCR task including polish letters using deep learning technique. The paper extends EMNIST dataset so that two new classes of polish diacritics “Ą” and “Ć” are attached. Using this new dataset and deep learning technique one can analyze sensitives of standard as well as presented extended approach with different parameters of convolutional neural network. The analysis of the results shows that the shadows and noises that Polish characters, leave with their hooks leads, can be properly recognized and two similar letters “A” and “Ą” can be distinguished by convolutional neural network. On the other hand a neural network trained on dataset without Polish characters do not treat letters “Ą” and “Ć” properly.
format	article
author	Dawid Grzelak Krzysztof Podlaski Grzegorz Wiatrowski
author_facet	Dawid Grzelak Krzysztof Podlaski Grzegorz Wiatrowski
author_sort	Dawid Grzelak
title	Analyze the effectiveness of an algorithm for identifying Polish characters in handwriting based on neural machine learning technologies
title_short	Analyze the effectiveness of an algorithm for identifying Polish characters in handwriting based on neural machine learning technologies
title_full	Analyze the effectiveness of an algorithm for identifying Polish characters in handwriting based on neural machine learning technologies
title_fullStr	Analyze the effectiveness of an algorithm for identifying Polish characters in handwriting based on neural machine learning technologies
title_full_unstemmed	Analyze the effectiveness of an algorithm for identifying Polish characters in handwriting based on neural machine learning technologies
title_sort	analyze the effectiveness of an algorithm for identifying polish characters in handwriting based on neural machine learning technologies
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/79e05652511b4c94aba610f87645420d
work_keys_str_mv	AT dawidgrzelak analyzetheeffectivenessofanalgorithmforidentifyingpolishcharactersinhandwritingbasedonneuralmachinelearningtechnologies AT krzysztofpodlaski analyzetheeffectivenessofanalgorithmforidentifyingpolishcharactersinhandwritingbasedonneuralmachinelearningtechnologies AT grzegorzwiatrowski analyzetheeffectivenessofanalgorithmforidentifyingpolishcharactersinhandwritingbasedonneuralmachinelearningtechnologies
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Analyze the effectiveness of an algorithm for identifying Polish characters in handwriting based on neural machine learning technologies

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