Université Blida 1

Détection de codes à barre de type 1D par l’apprentissage profond,Application au décodage de code à barres

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dc.contributor.author Hamel, Nadjet
dc.contributor.author Ziouane, Ferial
dc.date.accessioned 2023-09-20T13:35:33Z
dc.date.available 2023-09-20T13:35:33Z
dc.date.issued 2023
dc.identifier.uri https://di.univ-blida.dz/jspui/handle/123456789/24949
dc.description 4.621.1.1216 p:84 fr_FR
dc.description.abstract The objective of This Project is to realize a system that combines deep learning and image processing techniques for the detection, localization and decoding of 1D type barcodes. We used the YOLO V5 model, widely recognized for its accuracy and ability to detect objects in real time. At the same time, we applied advanced image processing techniques to precisely locate barcodes in an image and decipher them to extract the encoded information. We have also developed a user-friendly graphical interface to facilitate the use of our system. fr_FR
dc.language.iso fr fr_FR
dc.publisher blida 1 fr_FR
dc.subject Keywords : YOLO V5, Deep Learning, image processing , barcode. fr_FR
dc.title Détection de codes à barre de type 1D par l’apprentissage profond,Application au décodage de code à barres fr_FR


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