Static Image-based Emotion Recognition Using Convolutional Neural Network

Emotion recognition systems have been used frequently both socially and commercially. Various classification methods are used to perform emotion recognition. The convolutional neural network (CNN) has a popular position among these classification methods. The CNN modeling process, which is left to the user experience, is a hard challenging task. Instead of modeling a new system, transfer learning from pre-trained models often increases performance and prevents loss of time. In this paper, a new dataset, created with the help of image search engines, is classified with transfer learning supported CNN. Data preprocessing methods were also applied to increase classification success. The results obtained with experimental studies are presented in detail.