Abstract—In order to improve the recognition rate, this document proposes an automatic system to ... more Abstract—In order to improve the recognition rate, this document proposes an automatic system to recognize isolated printed Tifinagh characters by using a fusion of 3 classifiers and a combination of some features extraction methods. The Legendre moments, Zernike moments and Hu moments are used as descriptors in the features extraction phase due to their invariance to translation, rotation and scaling changes. In the classification phase, the neural network, the multiclass SVM (Support Vector Machine) and the nearest neighbour classifiers are combined together. The experimental results of each single features extraction method and each single classification method are compared with our approach to show its robustness.
After the era of the World Wide Web, information is easily accessible with a single click. But th... more After the era of the World Wide Web, information is easily accessible with a single click. But this progression has drawbacks despite the ease of access to information. Plagiarism has a growing challenge to society, which impact on the academic world, researchers, and students in particular. This work discusses the plagiarism process, types, and detection methodologies. It presents the different plagiarism detection techniques based on syntactic and semantic approaches. The result of this work is a comparative survey of plagiarism detection system methods using the identification of syntactic and semantic similarities based a sentence-to-sentence comparison, and no longer word-to-word like the classical systems because the similarity between the sentences is a complex phenomenon.
Abstract—In order to improve the recognition rate, this document proposes an automatic system to ... more Abstract—In order to improve the recognition rate, this document proposes an automatic system to recognize isolated printed Tifinagh characters by using a fusion of 3 classifiers and a combination of some features extraction methods. The Legendre moments, Zernike moments and Hu moments are used as descriptors in the features extraction phase due to their invariance to translation, rotation and scaling changes. In the classification phase, the neural network, the multiclass SVM (Support Vector Machine) and the nearest neighbour classifiers are combined together. The experimental results of each single features extraction method and each single classification method are compared with our approach to show its robustness.
After the era of the World Wide Web, information is easily accessible with a single click. But th... more After the era of the World Wide Web, information is easily accessible with a single click. But this progression has drawbacks despite the ease of access to information. Plagiarism has a growing challenge to society, which impact on the academic world, researchers, and students in particular. This work discusses the plagiarism process, types, and detection methodologies. It presents the different plagiarism detection techniques based on syntactic and semantic approaches. The result of this work is a comparative survey of plagiarism detection system methods using the identification of syntactic and semantic similarities based a sentence-to-sentence comparison, and no longer word-to-word like the classical systems because the similarity between the sentences is a complex phenomenon.
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Papers by R. El Ayachi