Torres, M., Rojas, L., Porras, D., Gamarra, J. (2024). Moodle plugin for real-time face recognition in online exams for Systems Engineering and Computer Science students at Universidad Continental, Huancayo, Peru [Universidad Continental]. https://hdl.handle.net/20.500.12394/14879
Torres, M., Rojas, L., Porras, D., Gamarra, J. Moodle plugin for real-time face recognition in online exams for Systems Engineering and Computer Science students at Universidad Continental, Huancayo, Peru []. PE: Universidad Continental; 2024. https://hdl.handle.net/20.500.12394/14879
@misc{renati/914125, title = "Moodle plugin for real-time face recognition in online exams for Systems Engineering and Computer Science students at Universidad Continental, Huancayo, Peru", author = "Gamarra Moreno, Job Daniel", publisher = "Universidad Continental", year = "2024" }
Título: Moodle plugin for real-time face recognition in online exams for Systems Engineering and Computer Science students at Universidad Continental, Huancayo, Peru
Campo OCDE: https://purl.org/pe-repo/ocde/ford#2.00.00
Fecha de publicación: 2024
Institución: Universidad Continental
Resumen: Facial recognition systems on learning platforms like Moodle
enable fast and efficient evaluation, automating the detection of
impersonation in online exams. This project implements a Moodle
plugin that performs facial recognition on the student attempting to
take a quiz. It consists of two parts for authentication through a
webcam: the first part occurs before accessing the quiz, and the
second part involves surveillance through a camera during the quiz.
The plugin was developed using the PHP and JavaScript
programming languages, as well as Face-api. The JavaScript API
detects and recognizes faces in the web browser using Tiny Yolo v2
and FaceRecognizerNet. It compares a student's photo or image with
the image from their webcam while they are taking the quiz. The
Moodle plugin achieved an average error probability of 39.39% for
face detection similarity distance.
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