A post COVID Machine Learning approach in Teaching and Learning methodology to alleviate drawbacks of the e-whiteboards

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 their mark as the state-of-the-art technology application which holds the epitome of a reasonable...

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Autores principales:	Sudan Jha, Sultan Ahmad, Hikmat A. M. Abdeljaber, A. A. Hamad, Malik Bader Alazzam
Formato:	article
Lenguaje:	EN
Publicado:	Tamkang University Press 2021
Materias:	learning transfer learning electronic whiteboard deep learning machine learning Engineering (General). Civil engineering (General) TA1-2040 Chemical engineering TP155-156 Physics QC1-999
Acceso en línea:	https://doaj.org/article/a829e86d999f48d097f42f907c18c507
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spelling	oai:doaj.org-article:a829e86d999f48d097f42f907c18c5072021-11-23T17:48:14ZA post COVID Machine Learning approach in Teaching and Learning methodology to alleviate drawbacks of the e-whiteboards10.6180/jase.202204_25(2).00142708-99672708-9975https://doaj.org/article/a829e86d999f48d097f42f907c18c5072021-11-01T00:00:00Zhttp://jase.tku.edu.tw/articles/jase-202204-25-2-0014https://doaj.org/toc/2708-9967https://doaj.org/toc/2708-9975Deep 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 their 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 a unison conclusion. This paper aims to target the drawbacks of the electronic whiteboard with a simultaneous focus on the suitable model selection procedure for the digit recognition problem.Sudan JhaSultan AhmadHikmat A. M. AbdeljaberA. A. HamadMalik Bader AlazzamTamkang University Pressarticlelearningtransfer learningelectronic whiteboarddeep learningmachine learningEngineering (General). Civil engineering (General)TA1-2040Chemical engineeringTP155-156PhysicsQC1-999ENJournal of Applied Science and Engineering, Vol 25, Iss 2, Pp 285-294 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	learning transfer learning electronic whiteboard deep learning machine learning Engineering (General). Civil engineering (General) TA1-2040 Chemical engineering TP155-156 Physics QC1-999
spellingShingle	learning transfer learning electronic whiteboard deep learning machine learning Engineering (General). Civil engineering (General) TA1-2040 Chemical engineering TP155-156 Physics QC1-999 Sudan Jha Sultan Ahmad Hikmat A. M. Abdeljaber A. A. Hamad Malik Bader Alazzam A post COVID Machine Learning approach in Teaching and Learning methodology to alleviate drawbacks of the e-whiteboards
description	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 their 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 a unison conclusion. This paper aims to target the drawbacks of the electronic whiteboard with a simultaneous focus on the suitable model selection procedure for the digit recognition problem.
format	article
author	Sudan Jha Sultan Ahmad Hikmat A. M. Abdeljaber A. A. Hamad Malik Bader Alazzam
author_facet	Sudan Jha Sultan Ahmad Hikmat A. M. Abdeljaber A. A. Hamad Malik Bader Alazzam
author_sort	Sudan Jha
title	A post COVID Machine Learning approach in Teaching and Learning methodology to alleviate drawbacks of the e-whiteboards
title_short	A post COVID Machine Learning approach in Teaching and Learning methodology to alleviate drawbacks of the e-whiteboards
title_full	A post COVID Machine Learning approach in Teaching and Learning methodology to alleviate drawbacks of the e-whiteboards
title_fullStr	A post COVID Machine Learning approach in Teaching and Learning methodology to alleviate drawbacks of the e-whiteboards
title_full_unstemmed	A post COVID Machine Learning approach in Teaching and Learning methodology to alleviate drawbacks of the e-whiteboards
title_sort	post covid machine learning approach in teaching and learning methodology to alleviate drawbacks of the e-whiteboards
publisher	Tamkang University Press
publishDate	2021
url	https://doaj.org/article/a829e86d999f48d097f42f907c18c507
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A post COVID Machine Learning approach in Teaching and Learning methodology to alleviate drawbacks of the e-whiteboards

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