id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_kti2eifb7rbd7peetif77jx5f4	Ebenezer Owusu	A neural-AdaBoost based facial expression recognition system	2014	8	.pdf	application/pdf	6511	947	63	The selected features were fed into a well designed 3-layer neural network classifier that is trained by a back-propagation algorithm. neural based facial expression recognition system that used principal component analysis (PCA) to reduce the feature vectors. Kumbhar, Jadhav, and Patil (2012) described a neural network classification facial expression recognition system that employs Gabor and Pawar (2012) extracted features of the face using Affine Moment Invariants and performed the classification using feed-forward neural network. extracted the expressive face by using Gabor filters, feature reduction by PCA and expression classification by neural network. expression classifier and extracted the facial features by Gabor filters and reduced the features via PCA. The Patch based feature extraction method is another alternative widely exploited for facial expression biometrics. The selected features represent samples of the facial deformation patterns of the expressive face. The selected features are fed into the constructed neural network to train it to identify the seven universal facial expressions.	./cache/work_kti2eifb7rbd7peetif77jx5f4.pdf	./txt/work_kti2eifb7rbd7peetif77jx5f4.txt