Mohammed Ouali

Work place: Department of Computer Science, College of Computers and Information Technology, Taif University, KSA



Research Interests: Computer systems and computational processes, Computer Vision, Pattern Recognition, Data Structures and Algorithms


Mohammed Ouali received the Doctor degree in Real Time Informatics, Robotics, and Automatic Control from Mines ParisTech, France, and the Ph.D. in Mathematics and Computer Science from Sherbrooke University, Canada.  Dr. Ouali has more than 15 years in both industry and academia. His research interests include signal processing, pattern recognition, big data, and computer vision.

Author Articles
An Optimization-Based Framework for Feature Selection and Parameters Determination of SVMs

By Seyyid Ahmed Medjahed Mohammed Ouali Tamazouzt Ait Saadi Abdelkader Benyettou

DOI:, Pub. Date: 8 Apr. 2015

In this paper, feature selection and parameters determination in SVM are cast as an energy minimization procedure. The problem of feature selection and parameters determination is a very difficult problem where the number of feature is very large and where the features are highly correlated. We define the problem of feature selection and parameters determination in SVM as a combinatorial problem and we use a stochastic method that, theoretically, guarantees to reach the global optimum. Several public datasets are employed to evaluate the performance of our approach. Also, we propose to use the DNA Microarray Datasets which are characterized by the large number of features. To validate our approach, we apply it to image classification. The feature descriptors of the images were extracted by using the Pyramid Histogram of Oriented Gradients. The proposed approach was compared with twenty feature selection methods. Experimental results indicate that the classification accuracy rates of the proposed approach exceed those of other approaches.

[...] Read more.
Other Articles