Deep Learning and Machine Learning based Facial Emotion Detection using CNN

Human emotions are the psychological conditions of sentiments that are encountered impulsively which imply the expressions on the face. By using Machine Learning and Deep Learning in this paper, the emotions will be detected and human behavior will be extracted. The various body language approaches like idiomatic expressions, eye stirring and body movement are significant while applying for the association between machines and people. Out of these methods, facial emotion is most commonly employed as it refers to the mental sentiments and frame of person's mind. The identification of the various emotions is sometimes a very difficult job as no specified prototype or framework is there to differentiate the various kinds of sentiments and also there are various complications while recognizing the facial emotion expression. Facial emotions are so much crucial in non-verbal type communication which appears to the internal feelings of an individual that reflects on the faces. Machine Learning techniques, Deep learning and Neural Network algorithms are used for emotion recognition. This work is going to propose an efficient technique using Convolutional Neural Networks (CNNs) to detect anger, disgust, happiness, fear, sadness, calmness and surprisingness.