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Automated Exam Proctoring using Support Vector Machine and Histogram of Oriented Gradients
1st International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2022 ; : 922-926, 2022.
Article in English | Scopus | ID: covidwho-1932078
ABSTRACT
Online learning has grown exponentially since the Covid-19 outbreak. Educational organizations are forced to stop their regular curriculum. Using remote communication software, students are able to pursue their educational curriculums. This paper proposes a multimedia exam proctoring system based on face recognition and object capturing systems. System hardware includes a webcam only. Dlib is used for facial detection and face landmark detection. The OpenCV Caffe model is then utilised to appropriately locate and sketch the face. YOLOv3 is used to detect objects. Onfocus event is used for tab detection. By combining all these, an exam proctoring system is developed which can classify if the student is found cheating and is then informed to the examiner. © 2022 IEEE.
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 1st International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2022 Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 1st International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2022 Year: 2022 Document Type: Article