Face expression recognition with a 2-channel Convolutional Neural Network

2015 ◽  
Author(s):  
Dennis Hamester ◽  
Pablo Barros ◽  
Stefan Wermter
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Expression Recognition ◽  
Face Expression ◽  
Face Expression Recognition

scholarly journals Face Expression Recognition using Convolution Neural Network (CNN) Models

2020 ◽  
Vol 11 (4) ◽  
pp. 1-11
Author(s):  
Nahla Nour ◽  
Mohammed Elhebir ◽  
Serestina Viriri
Keyword(s):  
Neural Network ◽  
Feature Extraction ◽  
Facial Expression ◽  
Facial Expression Recognition ◽  
Recognition Accuracy ◽  
Svm Classifier ◽  
Expression Recognition ◽  
Face Expression ◽  
Result Show ◽  
Face Expression Recognition

This paper proposes the design of a Facial Expression Recognition (FER) system based on deep convolutional neural network by using three model. In this work, a simple solution for facial expression recognition that uses a combination of algorithms for face detection, feature extraction and classification is discussed. The proposed method uses CNN models with SVM classifier and evaluates them, these models are Alex-net model, VGG-16 model and Res-Net model. Experiments are carried out on the Extended Cohn-Kanada (CK+) datasets to determine the recognition accuracy for the proposed FER system. In this study the accuracy of AlexNet model compared with Vgg16 model and ResNet model. The result show that AlexNet model achieved the best accuracy (88.2%) compared to other models.

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