Výsledky vyhledávání - "Naouar Belghini"

Learning a Backpropagation Neural Network With Error Function Based on Bhattacharyya Distance for Face Recognition

Autor: Jamal Kharroubi, Arsalane Zarghili, Aicha Majda, Naouar Belghini

Publikováno v: International Journal of Image, Graphics and Signal Processing. 4:8-14

In this paper, a color face recognition system is developed to identify human faces using Back propagation neural network. The architecture we adopt is All-Class-in-One-Network, where all the classes are placed in a single network. To accelerate the

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::f3025e89d3fcece81448e2226e6edd36
https://doi.org/10.5815/ijigsp.2012.08.02

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A gender classification approach based on 3D depth-radial curves and fuzzy similarity based classification

Autor: Soufiane Ezghari, Naouar Belghini, Arsalane Zarghili, Azeddine Zahi

Publikováno v: 2015 Intelligent Systems and Computer Vision (ISCV).

We propose in this paper, a gender recognition solution under the presence of occlusion and using the very restrict samples in the learning base. The developed approach is based on the extraction of pertinent 3D depth-radial curves that cover the nos

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::dd2bf31e561b67569b05faadd1c46bc1
https://doi.org/10.1109/isacv.2015.7106178

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3D face recognition using facial curves, sparse random projection and fuzzy similarity measure

Autor: Naouar Belghini, Soufiane Ezghari, Azeddine Zahi

Publikováno v: CIST

In this paper, we propose a fuzzy similarity based classification approach for 3D face recognition. In the feature extraction method, we exploit curve concept to represent the 3D facial data, two types of curves was considered: depth-level and depth-

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b525a2f91f29d3f7c3d2d8e06347b83a
https://doi.org/10.1109/cist.2014.7016639

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Autor: Arsalane Zarghili, Azeddine Zahi, Soufiane Ezghari, Naouar Belghini

Publikováno v: International Journal of Biometrics. 9:253

In this paper, we propose a new fuzzy similarity-based classification (FSBC) method for the task of gender recognition. The proposed method characterises each individual by extracting geometrical features from a 3D facial image using pertinent radial

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9746bb2197aae33dc5b457d6d195880e
https://doi.org/10.1504/ijbm.2017.10009328

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Face Detection and Recognition Using Back Propagation Neural Network and Fourier Gabor Filters

Autor: Jamal Kharroubi, Anissa Bouzalmat, Arsalane Zarghili, Naouar Belghini

Face recognition is a field of computer vision that uses faces to identify or verify a person. In this paper, we present a neural network system for face recognition. Feature vector based on Fourier Gabor filters are used as input of the Back Propaga

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b6940254834a2bc1240615378572e79a

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Color facial authentication system based on neural network

Autor: Jamal Kharroubi, Arsalane Zarghili, Aicha Majda, Naouar Belghini

Publikováno v: CIST

Face recognition can be defined as the ability of a system to classify or describe a human face. The motivation for such system is to enable computers to do things like humans do and to apply computers to solve problems that involve analysis and clas

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::9290adcc3a4ea66362b4f82fca4f0a2b
https://doi.org/10.1109/cist.2011.6148586

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A color facial authentification system based on semi supervised backporpagation neural network

Autor: Arsalane Zarghili, Jamal Kharroubi, Aicha Majda, Naouar Belghini

Publikováno v: 2011 International Conference on Multimedia Computing and Systems.

A Backpropagation Neural Network (BPNN) is one of the most used methods in the domain of face recognition. BPNN need supervised training to learn how to predict results from desired data, and through many research and studies, they proof there robust

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::abea98ecf32eff5ed4789f724b005eef
https://doi.org/10.1109/icmcs.2011.5945666

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