INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Exams are commonly used by educational institutions to evaluate students' strengths and weaknesses. However, students often cheat during physical exams by exchanging papers, using hidden notes, and fulfilling their parents' expectations, among other things. Due to physical limitations, traditional invigilation methods cannot effectively monitor exams while maintaining their integrity. To address this issue, this study proposes an automated method based on computer vision, which uses closed-circuit television (CCTV) cameras to detect suspicious behavior during physical exams. The proposed method employs You Only Look Once (YOLOv5) with residual networks as the backbone architecture to inspect cheating. The results demonstrate that the proposed method is credible and efficient, achieving 88.03% accuracy in detecting cheating in the classroom environment. Overall, this work shows promising results for invigilating students during exams.
Keywords:
Cheating Detection, Deep Learning, Object Detection, Smart Invigilation, YOLOv5.
Cite Article:
" Automatic cheating detection of exam hall", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 11, page no.a834-a843, November-2023, Available :http://www.ijnrd.org/papers/IJNRD2311094.pdf
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ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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