Emotions Classification Framework based on Facial Expressions

This article addresses the use of face feature extraction using a neural network in combination to identify various classification emotions (happy, sad, angry, fear, surprised, neutral etc.). When communicating, People have the ability to performing There are countless variations in the intricacy, intensity, and meaning of facial expressions. The limitations of the current feeling are investigated in this study. identification method that uses brain activity. In this research, I have used an existing simulator to produce findings that are 94% accurate. This method is simpler and then using a device that monitors brain activity for emotion recognition. The intended system is dependent on the human face since, as we are all aware, the face also conveys emotions or brain activity. Neural networks were utilized in this paper to achieve better results comparisons towards the end of the paper.