Effectiveness of artificial neural networks in recognising handwriting characters
Artificial neural networks are one of the tools of modern text recognising systems from images, including handwritten ones. The article presents the results of a computational experiment aimed at analyzing the quality of recognition of handwritten digits by two artificial neural networks (ANNs) wit...
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Lublin University of Technology
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doaj-f726119d901646ebb4835fd98a0875e52020-11-25T04:09:11ZengLublin University of TechnologyJournal of Computer Sciences Institute2544-07642018-09-01710.35784/jcsi.680Effectiveness of artificial neural networks in recognising handwriting charactersMarek Miłosz0 Janusz Gazda1Institute of Computer Science, Lublin University of Technology, Nadbystrzycka 36B, 20-618 Lublin, PolandInstitute of Computer Science, Lublin University of Technology, Nadbystrzycka 36B, 20-618 Lublin, Poland Artificial neural networks are one of the tools of modern text recognising systems from images, including handwritten ones. The article presents the results of a computational experiment aimed at analyzing the quality of recognition of handwritten digits by two artificial neural networks (ANNs) with different architecture and parameters. The correctness indicator was used as the basic criterion for the quality of character recognition. In addition, the number of neurons and their layers and the ANNs learning time were analyzed. The Python language and the TensorFlow library were used to create the ANNs, and software for their learning and testing. Both ANNs were learned and tested using the same big sets of images of handwritten characters. https://ph.pollub.pl/index.php/jcsi/article/view/680character recognition; handwriting; artificial neural networks |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Marek Miłosz Janusz Gazda |
spellingShingle |
Marek Miłosz Janusz Gazda Effectiveness of artificial neural networks in recognising handwriting characters Journal of Computer Sciences Institute character recognition; handwriting; artificial neural networks |
author_facet |
Marek Miłosz Janusz Gazda |
author_sort |
Marek Miłosz |
title |
Effectiveness of artificial neural networks in recognising handwriting characters |
title_short |
Effectiveness of artificial neural networks in recognising handwriting characters |
title_full |
Effectiveness of artificial neural networks in recognising handwriting characters |
title_fullStr |
Effectiveness of artificial neural networks in recognising handwriting characters |
title_full_unstemmed |
Effectiveness of artificial neural networks in recognising handwriting characters |
title_sort |
effectiveness of artificial neural networks in recognising handwriting characters |
publisher |
Lublin University of Technology |
series |
Journal of Computer Sciences Institute |
issn |
2544-0764 |
publishDate |
2018-09-01 |
description |
Artificial neural networks are one of the tools of modern text recognising systems from images, including handwritten ones. The article presents the results of a computational experiment aimed at analyzing the quality of recognition of handwritten digits by two artificial neural networks (ANNs) with different architecture and parameters. The correctness indicator was used as the basic criterion for the quality of character recognition. In addition, the number of neurons and their layers and the ANNs learning time were analyzed. The Python language and the TensorFlow library were used to create the ANNs, and software for their learning and testing. Both ANNs were learned and tested using the same big sets of images of handwritten characters.
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topic |
character recognition; handwriting; artificial neural networks |
url |
https://ph.pollub.pl/index.php/jcsi/article/view/680 |
work_keys_str_mv |
AT marekmiłosz effectivenessofartificialneuralnetworksinrecognisinghandwritingcharacters AT januszgazda effectivenessofartificialneuralnetworksinrecognisinghandwritingcharacters |
_version_ |
1724422899902709760 |