2692-4048ISSN (Online)
2770-0070ISSN (Print)
Volume 2 , Issue 2 , PP: 57-63, 2020 | Cite this article as | XML | Html | PDF | Full Length Article
Shubham Gupta 1 * , Aarushi Dhawan 2 , Arpit Gupta 3 , A. Kumar Dubey 4
Doi: https://doi.org/10.54216/FPA.020203
Human facial emotion recognition has attracted interest in the field of Artificial Intelligence. The emotions on a human face depict what's going on inside the mind. Facial expression recognition is the part of Facial recognition which is gaining more importance, and the need for it has increased tremendously. Though there are methods to identify expressions using machine learning and Artificial Intelligence techniques, this work attempts to use convolution neural networks to recognize expressions and classify the expressions into 6 emotional categories. Various datasets are investigated and explored for training expression recognition models are explained in this paper, and the models which are used in this paper are VGG 19 and RESNET 18. We included facial emotional recognition with gender identification also. In this project, we have used the fer2013 and ck+ datasets and ultimately achieved 73% and 94% around accuracies, respectively.
Facial Expression Recognition , Gender Identification
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