DC Field | Value | Language |
dc.contributor.author | REGGAM, MOunsif | - |
dc.date.accessioned | 2023-03-05T08:55:43Z | - |
dc.date.available | 2023-03-05T08:55:43Z | - |
dc.date.issued | 2022 | - |
dc.identifier.uri | https://repository.esi-sba.dz/jspui/handle/123456789/407 | - |
dc.description | Supervisor : Dr. KHALDI Belkacem | en_US |
dc.description.abstract | Face recognition is considered one of most important biometric used for many practical
uses such as security, law enforcement and commercialising. Because of this field’s importance,
researchers started showing an increasing interest in developing and improving
it. In this work, We aim to cover two dimensional and three dimensional face recognition
and their different deep learning based methods and datasets that are used for training
or testing.***La reconnaissance faciale est consid´er´ee comme l’une des biom´etries les plus importantes
utilis´ees pour de nombreuses pratiques quotidiennes et utilisations techniques telles
que la s´ecurit´e, l’application de la loi et la commercialisation. Suite `a cette importance,
les chercheurs ont commenc´e `a s’int´eresser par le d´eveloppement et l’am´elioration du domaine.
Dans ce travail, notre objectif est de d’explorer la reconaissance faciale en deux
et trois dimensions ainsi que leurs differntes m´ethodes bas´ees sur l’apprentissage profond
et base de donn´es utilis´ees pour l’entrainement ou pour tester. | en_US |
dc.language.iso | en | en_US |
dc.subject | Automated Learning | en_US |
dc.subject | Deep Learning | en_US |
dc.subject | Face Recognition | en_US |
dc.subject | Corporate Surveillance | en_US |
dc.subject | Neural Networks | en_US |
dc.subject | Access Control | en_US |
dc.title | Comparative Study Of Face Recognition Deep Learning Based Methods | en_US |
dc.type | Thesis | en_US |
Appears in Collections: | Master
|