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Please use this identifier to cite or link to this item: https://repository.esi-sba.dz/jspui/handle/123456789/559
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dc.contributor.authorTOUATI, ABderrahmane-
dc.date.accessioned2023-10-19T08:36:06Z-
dc.date.available2023-10-19T08:36:06Z-
dc.date.issued2023-
dc.identifier.urihttps://repository.esi-sba.dz/jspui/handle/123456789/559-
dc.descriptionSupervisor : Dr. Bensenane Hamdanen_US
dc.description.abstractAbstract : In recent years, biometric recognition, encompassing face recognition and fingerprint recognition, has emerged as a crucial field in modern technology. This thesis provides an extensive review of the state-of-the-art advancements in these two prominent biometric recognition techniques. The study examines the methodologies, challenges, and potential future directions in face recognition and fingerprint recognition. Face recognition has witnessed remarkable progress driven by machine learning and computer vision techniques, utilizing deep learning models and large-scale face databases. Fingerprint recognition, a widely adopted biometric technique, has seen advancements in algorithms and sensor technologies, particularly in minutiae-based matching algorithms and improved acquisition sensors. The thesis addresses challenges such as pose variations, illumination changes, and image quality, aiming to enhance the performance and reliability of biometric recognition systems. By analyzing the existing literature and evaluating different approaches, this research contributes to the advancement and improvement of face recognition and fingerprint recognition systems, making them more accurate and robust for various applications in security and identity verification domains. *** Résumé : Au cours des derni`eres ann´ees, la reconnaissance biom´etrique, comprenant la reconnaissance faciale et la reconnaissance des empreintes digitales, est devenue un domaine essentiel dans la technologie moderne. Cette th`ese offre une revue exhaustive des avanc´ees de pointe dans ces deux techniques de reconnaissance biom´etrique majeures. L’´etude examine les m´ethodologies, les d´efis et les orientations futures potentielles de la reconnaissance faciale et de la reconnaissance des empreintes digitales. La reconnaissance faciale a connu des progr`es remarquables grˆace aux techniques d’apprentissage automatique et de vision par ordinateur, en utilisant des mod`eles d’apprentissage profond et des bases de donn´ees de visages `a grande ´echelle. La reconnaissance des empreintes digitales, quant `a elle, repose sur des algorithmes de correspondance bas´es sur les minuties et des technologies de capteurs am´elior´ees. Cette th`ese aborde les d´efis tels que les variations de pose, les changements d’´eclairage et la qualit´e de l’image, dans le but d’am´eliorer les performances et la fiabilit´e des syst`emes de reconnaissance biom´etrique. En analysant la litt´erature existante et en ´evaluant diff´erentes approches, cette recherche contribue `a l’avancement et `a l’am´elioration des syst`emes de reconnaissance faciale et de reconnaissance des empreintes digitales, les rendant plus pr´ecis et plus fiables pour diverses applications dans les domaines de la s´ecurit´e et de la v´erification d’identit´e.en_US
dc.language.isoenen_US
dc.subjectBiometric Recognitionen_US
dc.subjectFace Recognitionen_US
dc.subjectFingerprint Recognitionen_US
dc.subjectMachine Learningen_US
dc.subjectDeep Learning Algorithmsen_US
dc.titleAdvancements in Deep Learning-Based Fingerprint and Facial Recognition: A State-of-the-Art Explorationen_US
dc.typeThesisen_US
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