APPLICATION OF ARTIFICAL INTELLIGENCE TO IDENTIFY THE STATE OF THE ELECTRIC METER
DOI:
https://doi.org/10.24867/23BE07DjuricKeywords:
Artifical intelligence, Machine learning, Deep learning, Neural networksAbstract
Scanning images and converting the scanned information into digital format is an active research area. Scanning is an automated, fast and efficient process as compared to traditional data entry. Recognizing digits from images is a challenging task. Traditional approaches to solve this problem typically separate the localization, segmentation, and recognition steps. This paper presents a unified approach that integrates these three steps via the use of a deep convolutional neural network that operates directly on the image pixels.
References
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[2] Muhammad Asif, Maaz Bin Ahmad, Shiza Mushtaq et al. “Long Multi-digit Number Recognition from Images Empowered by Deep Convolutional Neural Network”. The Computer Journal, Volume 65, Issue 10, October 2022, Pages 2815–2827. 13 September 2021.
[3] Tetko, I. V., Livingstone, D. J. and Luik, A. I. „Neural network studies. 1. Comparison of overfitting and overtraining,“ Journal of chemical information and computer sciences, 1995, 35.5: 826-833.
[4] Dietterich, T. „Overfitting and undercomputing in machine learning,“ ACM computing surveys (CSUR), 1995, 27.3: 326-327.
[5] Caruana, R., Lawrence, S., Giles, CL. „Overfitting in neural nets: Backpropagation, conjugate gradient, and early stopping.“ In: Advances in neural information processing systems. 2001. p. 402- 408.
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Published
2023-07-07
Issue
Section
Electrotechnical and Computer Engineering
