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3 articles for “Debias”
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AI Evaluator – Automated Examination Evaluation
Abstract: An AI system for automated exam grading is proposed. It tackles inefficiencies in human evaluation. The system uses TrOCR for accurate handwritten text recognition and a GPT model trained on graded responses for evaluation. This approach offers efficiency and reduced bias, but challenges remain. Evaluating open-ended questions and ensuring explainability require further development. It starts by looking at how AI technologies, such as machine learning, deep learning, and natural language …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 1, 2024 · pp. 1–9 Read article
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AI-Driven Exam Evaluation Systems: Challenges, Innovations, and Future Directions
Abstract: A proposed AI system is used to grade exams automatically. It addresses inefficiencies in human assessment. A GPT model trained on graded replies is used for evaluation, and TrOCR is used for precise handwritten text recognition. Efficiency and less bias are provided by this method, although there are still issues. More work is needed to assess open-ended questions and make sure they are understandable. To automate many aspects of exam …
Published in International Journal of Electronics Automation · Vol. 2, Issue 2, 2024 · pp. 7–13 Read article
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Bias Detection and Accuracy Enhancement in Voice-based Banking Authentication Using Deep Learning
Abstract: Biometric systems have become an integral part of how many people access banking services today, and voice verification systems can be a secure and easy-to-use source of banking authentication that does not require any physical contact with the bank or any other person. From the security perspective, these systems would normally provide an effective means of identifying an individual but frequently exhibit bias with respect to demographics such as the …
Published in International Journal of Information Security Engineering · Vol. 4, Issue 2, 2026 Read article