A predictive model to find out students facial emotion using Convolutional Neural Network
Keywords:
Facial expression, Emotion recognition, Expression Recognition, Fuzzy Inference System, AdaBoostAbstract
Emotion Recognition, also known as Facial Expression Recognition, is a valuable way to enhance the capabilities of current Human-Computer Interaction Technology. In this paper, we use the AdaBoost algorithm to determine class function parameters and then use a Fuzzy Conclusion System to develop a facial expression recognition system by first detecting the face from the background, rooting intriguing features from it, and finally classifying the face into one of five feelings: happy, horselaugh, sad, nausea, and neutral. With our outfit, we were able to achieve a success rate of 92.42 percent, which is really encouraging. All of the faces should have correct picture brightness and be in near-anterior exposures. The Indian Face Database was used.which was erected in 2002 by a group of IIT Kanpur scholars, for training purpose.
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