Published on: May 2026
AI EXAM CONTROLLER FOR QUESTION PAPER GENERATION AND ANSWER SHEET EVALUATION WITH SECURE RESULT PROCESSING
Parameshwari.P Yuvarani.M Yogeshwaran.M Sanjay.R Rajkumar.R
Gayathri
Tamilnadu India
Article Status
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Abstract
T5 Transformer. Scanned answer sheets are processed through OpenCV and Tesseract OCR, while semantic evaluation is performed using BERT embeddings and cosine similarity for accurate mark allocation. The evaluated marks are securely stored using blockchain technology to prevent tampering. The system supports COE verification and publishes results efficiently to colleges and students, ensuring accuracy, transparency, and reduced manual effort.
How to Cite this Paper
Parameshwari.P, , Yuvarani.M, , Yogeshwaran.M, , Sanjay.R, & Rajkumar.R, (2026). AI Exam Controller for Question Paper Generation and Answer Sheet Evaluation with Secure Result Processing. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(05). https://doi.org/10.55041/ijcope.v2i5.159
Parameshwari.P, , et al.. "AI Exam Controller for Question Paper Generation and Answer Sheet Evaluation with Secure Result Processing." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 05, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i5.159.
Parameshwari.P, , Yuvarani.M, Yogeshwaran.M, Sanjay.R, and Rajkumar.R. "AI Exam Controller for Question Paper Generation and Answer Sheet Evaluation with Secure Result Processing." International Journal of Creative and Open Research in Engineering and Management 02, no. 05 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i5.159.
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References
- Huo, N. Arabzadeh, and C. L. A. Clarke, “Retrieving supporting evidence for LLMs generated answers,” 2023, arXiv:2306.13781.
- Bolotova, V. Blinov, F. Scholer, W. B. Croft, and M. Sanderson, “A non-factoid question-answering taxonomy,” in Proc. 45th Int. ACM SIGIR Conf. Res. Develop. Inf. Retr., Jul. 2022, pp. 1196–1207.
- Rogers, M. Gardner, and I. Augenstein, “QA dataset explosion: A taxonomy of NLP resources for question answering and reading comprehension,” ACM Comput. Surveys, vol. 55, no. 10, pp. 1–45, Oct. 2023.
- Khoja and S. Ahmed, “UQuAD1.0: Development of an Urdu question answering training data for machine reading comprehension,” 2021, arXiv:2111.01543
- Arif, S. Farid, A. Athar, and A. A. Raza, “UQA: Corpus for Urdu question answering,” 2024, arXiv:2405.01458.
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- •Peer Review Type: Double-Blind Peer Review
- •Published on: May 06 2026
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