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The system should be able to detect students’ frontal faces in a classroom within 30% accuracy. The system should be able to automatically reveal the number of students present on a GUI. Recognise student stored on a database of faces by matching them to images on a database with an accuracy within 30%. The system should be able to match detected students faces cropped from an image to those on a database on the system. The system should be able to process an image within 10 minutes to be able to achieve the objective of recognition by
the end of a lecture. i.e. 5 names per hour per lecture. The algorithm implemented for the system’s functionality will achieve system accuracy within 20%. The positive prediction should be within 20%. The system designed will be user friendly with a Graphical User Interphase that will serve as an access to the functionalities of the system.

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