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Facial Emotion Recognition Using Shallow CNN

Publication Type : Conference Paper

Publisher : Springer Singapore

Source : Machine Learning and Metaheuristics Algorithms, and Applications, Springer Singapore, Singapore (2020)

Url :

ISBN : 9789811543012

Campus : Coimbatore

School : School of Engineering

Center : Computational Engineering and Networking

Department : Electronics and Communication

Year : 2020

Abstract : Facial emotional recognition became an important task in the modern day scenario to understand the state of emotions of a human being by machines. With the development of computational power and deep learning techniques, facial emotion recognition (FER) became feasible, which contributed to a wide range of applications in modern day technology. In this paper, we propose a shallow convolutional neural network architecture with feature-based data, which can do this task more effectively and attained the state-of-the-art accuracy with less computational complexity (in terms of learnable parameters). The proposed architecture is shallow and gives comparable performance with all the existing approaches for FER in deep learning.

Cite this Research Publication : T. K. Sachin Saj, Babu, S., Reddy, V. Kiran, Gopika, P., Sowmya, V., and Dr. Soman K. P., “Facial Emotion Recognition Using Shallow CNN”, in Machine Learning and Metaheuristics Algorithms, and Applications, Singapore, 2020.

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