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Inicio  /  Future Internet  /  Vol: 14 Par: 3 (2022)  /  Artículo
ARTÍCULO
TITULO

Neural Network-Based Price Tag Data Analysis

Pavel Laptev    
Sergey Litovkin    
Sergey Davydenko    
Anton Konev    
Evgeny Kostyuchenko and Alexander Shelupanov    

Resumen

This paper compares neural networks, specifically Unet, MobileNetV2, VGG16 and YOLOv4-tiny, for image segmentation as part of a study aimed at finding an optimal solution for price tag data analysis. The neural networks considered were trained on an individual dataset collected by the authors. Additionally, this paper covers the automatic image text recognition approach using EasyOCR API. Research revealed that the optimal network for segmentation is YOLOv4-tiny, featuring a cross validation accuracy of 96.92%. EasyOCR accuracy was also calculated and is 95.22%.

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