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Multimodal emotion recognition schema / Elham Shawky Salama Omer ; Supervised Reda Abdelwahab Ahmed Alkoribi , Mahmoud Ahmed Ismail Shoman , Mohammed Ahmed Wahby Shalaby

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Elham Shawky Salama Omer , 2020Description: 337 Leaves : charts , facsimiles , photoghrphs ; 30cmOther title:
  • مخطط للتعرف المتعدد الوسائل على التعبيرات [Added title page title]
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Dissertation note: Thesis (Ph.D.) - Cairo University - Faculty of Computure Artifical Intelligence - Department of Information Technology Summary: Many techniques were applied to improve the robustness of the multi-modal emotion recog-nition systems. In the proposed system ,anove lmulti modale motion recognition system using Electroencephalogram (EEG) signals ,and facial expression sisproposed .In this thesis, the 3- Dimensional Convolutional Neural Networks (3D-CNN)is in vestigated with the combination of theensemblelearningtechniques.SeveralexperimentalworksaretestedusingtheDEAP (Dataset of Emotion Analysis using the EEG, and Physiological ,and Video Signals)data. Three main recognition systems are built to achieve the proposed goal of this thesis. They are namely EEG-based emotion recognition system, face-based emotion recognition system ,and fusion-based emotion recognition system
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Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.20.01.Ph.D.2020.El.M (Browse shelf(Opens below)) Not for loan 01010110082831000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.20.01.Ph.D.2020.El.M (Browse shelf(Opens below)) 82831.CD Not for loan 01020110082831000

Thesis (Ph.D.) - Cairo University - Faculty of Computure Artifical Intelligence - Department of Information Technology

Many techniques were applied to improve the robustness of the multi-modal emotion recog-nition systems. In the proposed system ,anove lmulti modale motion recognition system using Electroencephalogram (EEG) signals ,and facial expression sisproposed .In this thesis, the 3- Dimensional Convolutional Neural Networks (3D-CNN)is in vestigated with the combination of theensemblelearningtechniques.SeveralexperimentalworksaretestedusingtheDEAP (Dataset of Emotion Analysis using the EEG, and Physiological ,and Video Signals)data. Three main recognition systems are built to achieve the proposed goal of this thesis. They are namely EEG-based emotion recognition system, face-based emotion recognition system ,and fusion-based emotion recognition system

Issued also as CD

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