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              <text>Enhanced Automated Online Examination Portal Using Convolutional Neural Network</text>
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              <text>Artificial Intelligence; Cloud Computing; Learning Management Systems; Machine Learning; Online Examination; Proctoring Systems</text>
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              <text>In recent years, the digital evolution of education has significantly shaped the landscape of learning, steering it away from traditional classroom settings towards more agile e-learning platforms. This shift has underscored the urgency for comprehensive online examination systems, tailored to meet the unique challenges and demands of virtual education. Online learning platforms have seen a rapid rise in popularity, given their flexibility, cost-effectiveness, and capability to cater to learners worldwide. Such a widespread audience brings along the challenge of conducting exams without the constraints of geography and scale. Traditional examinations, with their manual paper based formats, fail to fit within this digital mold due to their logistical challenges and inefficiencies. Consequently, an online examination system not only introduces convenience but also operational efficiency, eliminating many of the logistical nightmares associated with manual exams. While existing tools might provide online testing capabilities, the integration of Artificial Intelligent driven proctoring in this portal elevates the standards of academic integrity to unprecedented levels. The main aim of this article is to create online test platform with the support of Artificial Intelligence technology. The result detect the malpractice activity and electronic device usage detection while online examination.  2023 IEEE.</text>
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              <text>Vivek M.; Clintford P.S.; Prithvi R.; Maurya A.K.; Jayapandian N.</text>
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              <text>4th International Conference on Communication, Computing and Industry 6.0, C216 2023</text>
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              <text>Institute of Electrical and Electronics Engineers Inc.</text>
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              <text>&lt;a href="https://doi.org/10.1109/C2I659362.2023.10430811" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/C2I659362.2023.10430811&lt;/a&gt;
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              <text>ISBN: 979-835032732-8</text>
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              <text>Vivek M., Department of CSE, CHRIST (Deemed to be University), India; Clintford P.S., Department of CSE, CHRIST (Deemed to be University), India; Prithvi R., Department of CSE, CHRIST (Deemed to be University), India; Maurya A.K., School of Engineering and Technology, CHRIST (Deemed to be University), India; Jayapandian N., School of Engineering and Technology, CHRIST (Deemed to be University), India</text>
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