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Neural Networks : the Official Journal of the International Neural Network Society|January 10, 2021
An enhanced approach to the robust discriminant analysis and class sparsity based embeddingA Khoder, F Dornaika
Neural Networks : the Official Journal of the International Neural Network Society|May 4, 2020
Linear embedding by joint Robust Discriminant Analysis and Inter-class SparsityF Dornaika, A Khoder
IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society|October 7, 2004
Fast and reliable active appearance model search for 3-D face trackingF Dornaika, J Ahlberg
Neural Networks : the Official Journal of the International Neural Network Society|March 23, 2019
Joint sparse graph and flexible embedding for graph-based semi-supervised learningF Dornaika, Y El Traboulsi
IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society|February 2, 2008
Stereo geometry from 3D ego-motion streamsF Dornaika, C R Chung
Neural Networks : the Official Journal of the International Neural Network Society|February 29, 2024
Towards a unified framework for graph-based multi-view clusteringF Dornaika, S El Hajjar
Neural Networks : the Official Journal of the International Neural Network Society|August 13, 2017
Efficient dynamic graph construction for inductive semi-supervised learningF Dornaika, R Dahbi, A Bosaghzadeh, et al.
Neural Networks : the Official Journal of the International Neural Network Society|May 4, 2020
Graph Convolution Networks with manifold regularization for semi-supervised learningM Tavassoli Kejani, F Dornaika, H Talebi
Neural Networks : the Official Journal of the International Neural Network Society|February 8, 2025
Semi-supervised learning for multi-view and non-graph data using Graph Convolutional NetworksF Dornaika, J Bi, J Charafeddine, et al.
Neural Networks : the Official Journal of the International Neural Network Society|July 25, 2020
Feature fusion via Deep Random Forest for facial age estimationO Guehairia, A Ouamane, F Dornaika, et al.
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