Using CNN for facial expression recognition: a study of the effects of kernel size and number of filters on accuracy

• Published in: The Visual computer Vol. 36; no. 2; pp. 405 - 412
• Main Authors: Agrawal, Abhinav, Mittal, Namita
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.02.2020; Springer Nature B.V
• Subjects: Accuracy; Artificial Intelligence; Artificial neural networks; Classification; Computer Graphics; Computer Science; Data processing; Datasets; Deep learning; Face recognition; Image classification; Image Processing and Computer Vision; Machine learning; Neural networks; Original Article; Deep learning; FER-2013; CNN

Facial expression recognition is a challenging problem in image classification. Recently, the use of deep learning is gaining importance in image classification. This has led to increased efforts in solving the problem of facial expression recognition using convolutional neural networks (CNNs). A si...