Electrotechnical and Computer Engineering
Vol. 38 No. 07 (2023): Proceedings of Faculty of Technical Sciences
APPLICATION OF ARTIFICAL INTELLIGENCE TO IDENTIFY THE STATE OF THE ELECTRIC METER
Abstract
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.
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