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              <text>A post covid machine learning approach in teaching and learning methodology to alleviate drawbacks of the e-whiteboards</text>
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          <name>Subject</name>
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              <text>Deep Learning; Electronic Whiteboard; Learning; Machine Learning; Transfer Learning</text>
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              <text>Deep learning has paved the way for critical and revolutionary applications in almost every field of life in general. Ranging from engineering to healthcare, machine learning and deep learning has left its mark as the state-of-the-art technology application which holds the epitome of a reasonable high benchmarked solution. Incorporating neural network architectures into applications has become a common part of any software development process. In this paper, we perform a comparative analysis on the different transfer learning approaches in the domain of hand-written digit recognition. We use two performance measures, loss and accuracy. We later visualize the different results for the training and validation datasets and reach to a unison conclusion. This paper aims to target the drawbacks of the electronic whiteboard with simultaneous focus on the suitable model selection procedure for the digit recognition problem.  2021 Tamkang University. All Rights Reserved.</text>
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          <name>Creator</name>
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              <text>Jha S.; Ahmad S.; Abdeljaber H.A.M.; Hamad A.A.; Alazzam M.B.</text>
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              <text>Journal of Applied Science and Engineering, Vol-25, No. 2, pp. 285-294.</text>
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          <name>Publisher</name>
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              <text>Tamkang University</text>
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          <name>Date</name>
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              <text>2022-01-01</text>
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              <text>&lt;a href="https://doi.org/10.6180/jase.202204_25(2).0014" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.6180/jase.202204_25(2).0014&lt;/a&gt;
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          <name>Rights</name>
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              <text>Restricted Access</text>
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              <text>ISSN: 27089967</text>
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              <text>Online</text>
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              <text>English</text>
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              <text>Jha S., School of Sciences, Christ (Deemed to be University), NCR-New Delhi Campus, India; Ahmad S., Department of Computer Science, College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University, Alkharj, 11942, Saudi Arabia; Abdeljaber H.A.M., Department of Computer Science, College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University, Alkharj, 11942, Saudi Arabia; Hamad A.A., College of Science, Tikrit University, Iraq; Alazzam M.B., Faculty of Computer Science and Informatics, Amman Arab University, Jordan</text>
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