ONE SOLUTION OF OPTICAL CHARACTER RECOGNITION USING DEEP NEURAL NETWORKS
DOI:
https://doi.org/10.24867/16BE31IkonicKeywords:
Deep learning, Artificial intelligence, Neural networksAbstract
This paper presents one approach of automated optical character recognition on photographs with streetlights identification using deep Convolutional Neural Network. The task was realized in three iterations, with an accuracy of 93.04%.
References
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[2] S. Ali, Z. Shaukat, M. Azeem, Z. Sakhawat, T. Mahmood, K. ur Rehman: "An efficient and improved scheme for handwritten digit recognition based on convolutional neural network", SN Applied Sciences, Springer Nature Switzerland, vol. 1, art. 1125, pp. 1-9, 2019.
[3] D.C. Ciresan, A. Giusti, L.M. Gambardella, J. Schmidhuber: "Deep Neural Networks Segment Neuronal Membranes in Electron Microscopy Images", Advances in neural information processing systems, Lake Tahoe, Nevada, United States, 2012.
[4] S. Gavran: "Veštačke neuronske mreže u istraživanju podataka: pregled i primena", Univerzitet u Beogradu, Matematički fakultet, Master rad, 2016.
[5] https://github.com/mdbloice/Augmentor (pristupljeno u septembru 2021.)
[6] A. Krizhevsky, I. Sutskever, G.E. Hinton: "Imagenet classification with deep convolutional neural networks", Communications of the ACM, Association for Computing Machinery, vol. 60, issue 6, pp. 84–90, 2017.
[7] S. Hassanpour, N. Tomita, T. DeLise, B. Crosier, L. A. Marsch: "Identifying substance use risk based on deep neural networks and Instagram social media data", Neuropsychopharmacol, Springer Nature, vol. 44, pp. 487–494, 2019.
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Published
2022-02-04
Issue
Section
Electrotechnical and Computer Engineering
