Deep learning for classification of noisy QR codes

Autor:	Leygonie, Rebecca, Lobry, Sylvain, (LIPADE), Laurent Wendling
Jazyk:	francouzština
Rok vydání:	2023
Předmět:	Computer Science - Machine Learning Computer Science - Computer Vision and Pattern Recognition
Druh dokumentu:	Working Paper
Popis:	We wish to define the limits of a classical classification model based on deep learning when applied to abstract images, which do not represent visually identifiable objects.QR codes (Quick Response codes) fall into this category of abstract images: one bit corresponding to one encoded character, QR codes were not designed to be decoded manually. To understand the limitations of a deep learning-based model for abstract image classification, we train an image classification model on QR codes generated from information obtained when reading a health pass. We compare a classification model with a classical (deterministic) decoding method in the presence of noise. This study allows us to conclude that a model based on deep learning can be relevant for the understanding of abstract images. Comment: in French language. RFIAP 2022 - Reconnaissance des Formes, Image, Apprentissage et Perception, Jul 2022, Vannes (Bretagne), France
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2307.10677 Zobrazit plný text záznamu View this record from Arxiv