A CNN based facial expression recognizer

Facial expression recognition [FER] has gained attraction among many researchers in the field of artificial intelligence. The existing models available for facial expression recognition are developed with the help of native machine learning models. But the accuracies and efficiency achieved by these...

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Bibliographic Details
Main Authors: Teja, B. Sai Mani, Anita, C.S., Rajalakshmi, D., Berlin, M.A.
Format: Conference Proceeding
Language:English
Subjects:
Algorithms
Artificial intelligence
Convolutional neural networks
Deep learning
Facial expression recognition
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Summary:Facial expression recognition [FER] has gained attraction among many researchers in the field of artificial intelligence. The existing models available for facial expression recognition are developed with the help of native machine learning models. But the accuracies and efficiency achieved by these models are still undergoing extensive research. The proposed research work uses Convolutional Neural Networks (CNN) deep learning models with sufficient Computational power to run the algorithms. This model is able to achieve good accuracy even on the new datasets. Our experimental results achieved an accuracy of 57% in a five-classification task.
ISSN:2214-7853
2214-7853
DOI:10.1016/j.matpr.2020.08.501