A CASE STUDY ON FACE EMOTION RECOGNITION USING MACHINE LEARNING

Abstract

In the field of human-computer interaction, the identification of human emotions has proven to be a challenging task. TensorFlow only accepts data in the form of tensors, which are larger multidimensional arrays. In order to manage massive volumes of data, multi-dimensional arrays come in quite helpful. Distributed computing is the main advantage of TensorFlow, which is incredibly adaptable. Another algorithm evaluated is the standard one that is Keras, the deep learning models built with Keras can be created simply and quickly using TensorFlow because to its basic structure. Deep learning model definition is made simple with Keras for deep learning applications.