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040			_cIIITMK
100			_aRajalekshmi M. G. (93517010) _914513
245			_aFacial expression recognition system with five layer convolution neural network
300			_aMPhil CS 2017-2018
500			_aAbstract Now a days facial expression recognition field is growing and playing important role in communication. Facial expression recognition has been an active research area in the past ten years, with growing application areas including avatar animation, neuro marketing and sociable robots. The recognition of facial expressions is not an easy problem for machine learning methods, since people can vary significantly in the way they show their expressions. However, facial expressions change so subtly that recognition accuracy of most largely depend on feature extraction. In this work, we propose two independent methods for this very task. The first method uses facial expression recognition system using with five layer convolutional neural network, while the second method is an 8-layer convolutional neural network (CNN) or Alex net.In the first method to achieve facial expression recognition based on a deep CNN. Firstly we implement face detection by using Haar-like features and histogram equalization. Then we construct a five-layer CNN architecture, including two convolutional layers and two subsampling layers (C-S-C-S). Finally, a Softmax classifier is used for multi- classification.Second method,created an 8-layer CNN with five convolutional layers, and three fully connected layers. This module, to reduce redundancy of same features learned, considers mutual information between filters of the same layer, and processes the best set of features for the next layer.
502			_bMPhil CS _c2017-2018 _dINT _eDr. Elizabeth Sherly
650			_aFACIAL EXPRESSION RECOGNITION _914514
650			_aCNN _914515
650			_aMACHINE LEARNING _914516
942			_2ddc _cPR
999			_c6158 _d6158