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http://dlibrary.univ-boumerdes.dz:8080/handle/123456789/3913
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| Titre: | Face recognition using convolutional neural networks |
| Auteur(s): | Azizi, Narimene
Benselim, Mohammed Amine |
| Mots-clés: | Face recognition system
Convolutional neural network |
| Date de publication: | 2017 |
| Editeur: | Université M’Hamed BOUGARA de Boumerdes : Institut de génie electrique et electronique (IGEE) |
| Résumé: | Face Recognition is a currently developing technology with multiple real-life
applications. Deep learning, in particular Convolutional Neural Networks, has achieved
promising results in Face Recognition recently.
The goal of this project is to implement a complete Face Recognition system based on
state-of-the art Convolutional Neural Networks, and to test it on effected images in unconstrained environments. Relevant facial features are extracted and used to
determine if pairs of face images belong to the same individual or not. These features
allow to compare faces between them in an efficient way. The system is trained using
two different datasets, Faces94 and FaceScrub, resulting in two models. The "Labeled Faces in the Wild" benchmark is used for testing and evaluating the performance of the
two models. A comparison with classical methods is also done. |
| Description: | 56 p. |
| URI/URL: | http://dlibrary.univ-boumerdes.dz:8080/handle/123456789/3913 |
| Collection(s) : | Computer
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