Effectiveness of artificial neural networks in recognising handwriting characters


Abstract

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.


Keywords

character recognition; handwriting; artificial neural networks

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Published : 2018-09-30


Miłosz, M., & Gazda, J. (2018). Effectiveness of artificial neural networks in recognising handwriting characters. Journal of Computer Sciences Institute, 7, 210-214. https://doi.org/10.35784/jcsi.680

Marek Miłosz  m.milosz@pollub.pl
Institute of Computer Science, Lublin University of Technology, Nadbystrzycka 36B, 20-618 Lublin, Poland  Poland
Janusz Gazda 
Institute of Computer Science, Lublin University of Technology, Nadbystrzycka 36B, 20-618 Lublin, Poland  Poland