EMOTION CLASSIFICATION – DEEP LEARNING

Detecting the emotions using facial features is useful in the various fields. The convolutional neural network is a class of deep neural networks commonly applied to analyze and help to detect images. Here it’s been used for facial emotion recognition such as human facial expressions, facial features, and emotions of faces Sequential forward selection algorithms and soft-max activation function are also done in ordering the emotions and finding out in which emotion it belongs. So that this study can easily get a person’s feedback without any hindrance or lie from individuals and also this study can easily overcome the language barrier there are four types of datasets used here which are happy, sad, neutral, and angry. As a result of this study we got Ninety eight percent of accuracy in the future this study is expecting to add two more dataset which is guilt and fear so that it will also help us to detect criminals