Face recognition is very important topic because of its applications. The purpose of this work is developing a system that can recognize a person and register postgraduate students' attendance at faculty of specific education, Damietta University, Egypt. The proposed system consists of five stages: image acquisition, face detection, pre-processing, features extraction and classification. Image acquisition to capture real-time images. Face detection to detect face region from the image. Pre-processing stage involve the effective way of suppressing the unwanted distortion of image. Feature
Instructor evaluation is an important field in the educational process because it develops the level of instructor which can improve the educational level of students consequently. In this work, intelligent techniques are used for instructor performance evaluation in Arabic. This study used group of Arab lecturers through YouTube websitefor testing this system. The proposed system converts instructor's speech (system inputs) to text, and then analyzes the text to extract related knowledge for instructor evaluation that depends on a set of criteria, finally provides advice to the instructor (system outputs). Experimental results demonstrate the effectiveness of the proposed system in instructor performance evaluation. The proposed system can improve reliability and efficiency of instructors' performance; provide the basis for performance improvement that will affect students' academic outcomes.
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