Open Access
| Issue |
ITM Web Conf.
Volume 84, 2026
2026 International Conference on Advent Trends in Computational Intelligence and Data Science (ATCIDS 2026)
|
|
|---|---|---|
| Article Number | 04006 | |
| Number of page(s) | 8 | |
| Section | Computer Vision, Robotic Systems, and Intelligent Control | |
| DOI | https://doi.org/10.1051/itmconf/20268404006 | |
| Published online | 06 April 2026 | |
- L. C. O. Tiong, H. J. Lee. E-cheating prevention measures: Detection of cheating at online examinations using deep learning approach – a case study. arXiv Preprint (2021). https://doi.org/10.48550/arXiv.2101.09841 [Google Scholar]
- Z. Trabelsi, M. M. A. Parambil, F. Alnajjar, L. Ali. Behavioral-based real-time cheating detection in academic exams using deep learning techniques. AIP Conference Proceedings, Article 040006 (2023). https://doi.org/10.1063/5.0181921 [Google Scholar]
- B. Erdem, M. Karabatak.Cheating detection in online exams using deep learning and machine learning.Applied Sciences, 15(1), 400 (2025). https://doi.org/10.3390/app15010400 [Google Scholar]
- T. Potluri, S. Venkatramaphanikumar, K. V. K. Kishore. An automated online proctoring system using Attentive-Net to assess student mischievous behavior. Multimedia Tools and Applications, 82(20), 30375–30404 (2023). https://doi.org/10.1007/s11042-023-14604-w [Google Scholar]
- A. N. A. Thohari, M. F. Lathief, L. Triyono, K. Santoso. Exam cheating detection in closed room using YOLOv8 algorithm. Journal of Computer Science and Informatics Engineering, 4(2), 61–71 (2025). https://doi.org/10.55537/cosie.v4i2.1100 [Google Scholar]
- L. C. O. Tiong, H. J. J. Lee, K. L. Lim. Online assessment misconduct detection using Internet Protocol and behavioural classification. arXiv Preprint (2022). https://doi.org/10.48550/arXiv.2201.13226 [Google Scholar]
- F. Ozdamli, A. Aljarrah, D. Karagozlu, M. Ababneh. Facial recognition system to detect student emotions and cheating in distance learning. Sustainability, 14(20), Article 13230 (2022). https://doi.org/10.3390/su142013230 [Google Scholar]
- Z. Hu, Y. Jing, G. Wu, H. Wang. Multi-perspective adaptive paperless examination cheating detection system based on image recognition. Applied Sciences, 14(10), 4048 (2024). https://doi.org/10.3390/app14104048 [Google Scholar]
- G. Akçapınar. Detecting AI-assisted cheating in online exams through behavior analytics. arXiv Preprint (2025). https://doi.org/10.48550/arXiv.2510.18881 [Google Scholar]
- J.-Y. Zhu, T. Park, P. Isola, A. A. Efros. Unpaired image-to-image translation using cycle-consistent adversarial networks. Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2223–2232 (2017) [Google Scholar]
- T. Karras, S. Laine, T. Aila. A style-based generator architecture for generative adversarial networks. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 4401–4410 (2019). https://doi.org/10.1109/CVPR.2019.00453 [Google Scholar]
- T. Karras, S. Laine, M. Aittala, J. Hellsten, J. Lehtinen, T. Aila. Analyzing and improving the image quality of StyleGAN. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 8107–8116 (2020). https://doi.org/10.1109/CVPR42600.2020.00813 [Google Scholar]
- T. Kynkäänniemi, T. Karras, S. Laine, J. Lehtinen, T. Aila. Improved precision and recall metric for assessing generative models. arXiv Preprint (2019). https://doi.org/10.48550/arXiv.1904.06991 [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.