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Hybrid approach to recognize learners behaviors using facial expressions and machine learning / Mohammed Megahed Hussein Megahed ; Supervised Ammar Mohammed , Ahmed Hamza

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Mohammed Megahed Hussein Megahed , 2020Description: 115 Leaves : charts , facsimiles ; 30 LeavesOther title:
  • أسلوب تكاملى للتعرف على سلوك المتعلم بإستخدام إسلوب تحديد تعبيرات الوجه وتعلم الآلة [Added title page title]
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Dissertation note: Thesis (M.Sc.) - Cairo University - Faculty of Graduate Studies for Statistical Research - Department of Computer and Information Science Summary: Computer based learning environments are technology based instructional tools used for educational purpose. Usually, these environments take into consideration the learner's mental responses that are based on solving tests and exams questions to determine the next level of the learning process and manage the learning flow of the learner.They however suffer from engaging the emotional behaviors and facial expressions of the learner that reflect the learner's emotional states during the learning process.The later engagement could make the learning flow more adaptive as each learner could be redirected to a learning flow that matches his capabilities and academic performance.This thesis proposes a novel approach for modeling an adaptive computer based learning environment by considering the integration between the learner mental responses to exams questions and his emotional states during the exam sessions. In the proposed approach, a convolutional neural network is used to detect and analyze the learners' facial expressions, and outperforms other CNN models on the same training benchmark.The fuzzy system is used to determine the next learning level based on several response and interaction factors of the learner including emotional interaction factors and mental responses factors. The thesis also introduces corpora for evaluating the performance of the proposed approach
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Item type Current library Home library Call number Copy number Status Date due Barcode
Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.18.02.M.Sc.2020.Mo.H (Browse shelf(Opens below)) Not for loan 01010110080986000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.18.02.M.Sc.2020.Mo.H (Browse shelf(Opens below)) 80986.CD Not for loan 01020110080986000

Thesis (M.Sc.) - Cairo University - Faculty of Graduate Studies for Statistical Research - Department of Computer and Information Science

Computer based learning environments are technology based instructional tools used for educational purpose. Usually, these environments take into consideration the learner's mental responses that are based on solving tests and exams questions to determine the next level of the learning process and manage the learning flow of the learner.They however suffer from engaging the emotional behaviors and facial expressions of the learner that reflect the learner's emotional states during the learning process.The later engagement could make the learning flow more adaptive as each learner could be redirected to a learning flow that matches his capabilities and academic performance.This thesis proposes a novel approach for modeling an adaptive computer based learning environment by considering the integration between the learner mental responses to exams questions and his emotional states during the exam sessions. In the proposed approach, a convolutional neural network is used to detect and analyze the learners' facial expressions, and outperforms other CNN models on the same training benchmark.The fuzzy system is used to determine the next learning level based on several response and interaction factors of the learner including emotional interaction factors and mental responses factors. The thesis also introduces corpora for evaluating the performance of the proposed approach

Issued also as CD

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