Malpractice Detection in Examination Hall using Deep Learning

Title

Malpractice Detection in Examination Hall using Deep Learning

Creator

Aruna S.K.; Madhumitha A.; Shanmugam S.K.; Thangavel S.K.; Chang M.

Description

Various institutions administer tests at designated examination locations, chosen third-party and approved centers, and have established standards for installing CCTV cameras and conducting frisking under the supervision of designated personnel. Some institutions are using online proctoring, which enables students to take exams from any location. In all of the aforementioned scenarios, human monitoring is conducted, and maintaining a high level of vigilance may be challenging due to administrative oversight or intentional allowance of malpractice for personal gain. The malpractice detection may be attributed to acts like as plagiarism, unauthorized sharing of papers, and non-verbal communication. The study is conducted by capturing the dataset in the classroom of Christ University. The proposed approach is based on the YOLO framework. The movies are processed in real time to identify hand rotation, paper extraction, and classify the motion. The accuracy for the Head_right class is significantly higher than that of the Head_left class. The system is implemented using the programming language Python and has the potential for future expansion to provide real-time monitoring. 2024 IEEE.

Source

Proceedings - 2024 2nd International Conference on Inventive Computing and Informatics, ICICI 2024, pp. 286-291.

Date

2024-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

deep learning; Feature extraction; Human monitoring; Malpractice detection; YOLO

Coverage

Aruna S.K., CHRIST University, School of Engineering and Technology, Bangalore, Department of Computer Science and Engineering, India; Madhumitha A., CHRIST University, School of Engineering and Technology, Bangalore, Department of Computer Science and Engineering, India; Shanmugam S.K., Ashland University, Department of Mathematics and Computer Science, OH, United States; Thangavel S.K., Amrita Vishwa Vidyapeetham, Amrita School of Computing, Coimbatore, Department of Computer Science and Engineering, India; Chang M., Athabasca University, School of Computing Information and Systems, Canada

Rights

Restricted Access

Relation

ISBN: 979-835037329-5

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/ICICI62254.2024.00054

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85206000518&doi=10.1109%2fICICI62254.2024.00054&partnerID=40&md5=621c8dff24fefd1f6d27ebb12a719188