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dc.contributor.authorHamel, Nadjet-
dc.contributor.authorZiouane, Ferial-
dc.date.accessioned2023-09-20T13:35:33Z-
dc.date.available2023-09-20T13:35:33Z-
dc.date.issued2023-
dc.identifier.urihttps://di.univ-blida.dz/jspui/handle/123456789/24949-
dc.description4.621.1.1216 p:84fr_FR
dc.description.abstractThe 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.isofrfr_FR
dc.publisherblida 1fr_FR
dc.subjectKeywords : YOLO V5, Deep Learning, image processing , barcode.fr_FR
dc.titleDétection de codes à barre de type 1D par l’apprentissage profond,Application au décodage de code à barresfr_FR
Collection(s) :Mémoires de Master

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