000			02084cam a2200337 a 4500
003			EG-GiCUC
005			20250223032710.0
008			210301s2020 ua dho f m 000 0 eng d
040			_aEG-GiCUC _beng _cEG-GiCUC
041	0		_aeng
049			_aDeposite
097			_aPh.D
099			_aCai01.20.01.Ph.D.2020.El.M
100	0		_aElham Shawky Salama Omer
245	1	0	_aMultimodal emotion recognition schema / _cElham Shawky Salama Omer ; Supervised Reda Abdelwahab Ahmed Alkoribi , Mahmoud Ahmed Ismail Shoman , Mohammed Ahmed Wahby Shalaby
246	1	5	_aمخطط للتعرف المتعدد الوسائل على التعبيرات
260			_aCairo : _bElham Shawky Salama Omer , _c2020
300			_a337 Leaves : _bcharts , facsimiles , photoghrphs ; _c30cm
502			_aThesis (Ph.D.) - Cairo University - Faculty of Computure Artifical Intelligence - Department of Information Technology
520			_aMany 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
530			_aIssued also as CD
653		4	_aAverage filter
653		4	_aElectro-encephalogram EEG
653		4	_aMultimodal emotion recognition schema
700	0		_aMahmoud Ahmed Ismail Shoman , _eSupervisor
700	0		_aReda Abdelwahab Ahmed Alkoribi , _eSupervisor
856			_uhttp://172.23.153.220/th.pdf
905			_aNazla _eRevisor
905			_aShimaa _eCataloger
942			_2ddc _cTH
999			_c80062 _d80062