Abstract
Throughout the various ages, facial expressions have become one of the universal ways of non-verbal communication. The ability to recognize facial expressions would pave the path for many novel applications. Despite the success of traditional approaches in a controlled environment, these approaches fail on challenging datasets consisting of partial faces. In this paper, I take one such dataset FER-2013 and will implement deep learning models that are able to achieve significant improvement over the previously used traditional approaches and even some of the deep learning models.