چكيده به لاتين
Emotions are an inevitable portion of any inter-personal communication. Naturally, the human face as an indicator, represents the inner feelings and emotions of human beings.There has been an increase in the need to detect a person’s emotions in the past few years. There has been interest in human emotion recognition in various fields including human-computer interface, medicine, and security. Despite many advances in machine learning and deep learning, lack of acceptable accuracy, especially in uncontrolled images, has led to continued efforts in this area. Unlike classical facial recognition methods, which are based on the feature extraction, feature selection, and classification, in deep learning methods, the feature extraction and classification are merged. In this project, a method based on a combination of machine leraning and deep leraning is presented, which uses the trained deep network to extract the feature. Then the feature vectors are selected by the particle swarm optimization algorithm and Poor features are removed. Finally, the remaining features are classified by support vector machine. The accuracy of face recognition with this method on FER2013 database reached 70.4 percent.
