FACIAL EMOTION RECOGNITION FOR DUSKY SKINNED PEOPLE USING CNN
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FACIAL EMOTION RECOGNITION FOR DUSKY SKINNED PEOPLE USING CNN
Dr. S. Nandagopal1, P. Suriya2, M. Vanmathi3, V. Vetriselvi4
1 Professor, Department of Information Technology, Nandha College of Technology, Erode-638052, Tamil Nadu, India.
2,3,4 UG Students - Final Year, Department of Information Technology, Nandha College of Technology, Erode-638052, Tamil Nadu, India.
ABSTRACT - In computer vision, the Convolutional Neural Network is a very popular and useful model for emotion recognition. So, we are using the one of the CNN architectures to analyse the emotions called VGGNet. It is one of the methods or models of Transfer Learning Technology. It has more layers than its predecessors ImageNet and ResNet which have minimal layers when compared to VGGNet. It has 16 or 19 layers in its model to train the dataset. It can train a large dataset at a time. Our main goal is to accurately recognize the dusky skinned people's emotions. And so, for that we have used more sample images of dusky skinned people to be trained with the existing one. By doing so, we can improve the identification of emotions on dusky skinned people. And VGGNet technology also provide a great support to the improvement of the concept.
Keywords: Convolutional Neural Network (CNN), VGGNet architecture, facial emotion recognition, dusky skin.
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