A Formal Facial Expression Recognition System Using Novel Scattered Image Classification by Comparing CNN over Alexnet

Abstract

Aim:This study article's major goal is to classify facial expressions more accurately by utilizing Convolutional Neural
Networks (CNNs) in contrast to AlexNet. Materials and Methods: The data of the facial expressions is taken from the FER2013 available on kaggle.The Convolutional neural network (CNN) is the algorithm most common method of visual analysis with best accuracy and Alexney is also an algorithm used here to compare the accuracy of novel image classification. Results: The Convolution neural network (CNN) produces 82% accuracy in predicting facial expressions on the dataset,whereas AlexNet produces 76% accuracy. Convolutional neural network (CNN) is better than AlexNet.The study groups differ from one another in a statistically significant way (p <0.05).
Conclusion: Convolutional Neural Network provides better outcomes in accuracy rate when compared to AlexNet for predicting facial expressions.