Fast and robust online-learning facial expression recognition and innate novelty detection capability of extreme learning algorithms

2021 ◽  
Author(s):  
Sarutte Atsawaraungsuk ◽  
Tatpong Katanyukul ◽  
Pattarawit Polpinit ◽  
Nawapak Eua-anant
Keyword(s):  
Online Learning ◽  
Facial Expression ◽  
Facial Expression Recognition ◽  
Novelty Detection ◽  
Learning Algorithms ◽  
Expression Recognition ◽  
Detection Capability

scholarly journals Facial Expression Recognition using Ensemble Learning Technique

2019 ◽  
Vol 8 (4) ◽  
pp. 10274-10278
Keyword(s):  
Facial Expression ◽  
Ensemble Learning ◽  
Facial Expression Recognition ◽  
Learning Algorithms ◽  
Predictive Performance ◽  
Recognition System ◽  
Training Dataset ◽  
Expression Recognition ◽  
Ensemble Technique ◽  
Learning Technique

The most natural, influential and powerful way to communicate or convey a message is face expressions. In the field of computer engineering, facial expression recognition system, is helpful in areas like healthcare system, computer graphics, biometric devices, mobile phones, etc. Technologies such as virtual reality (VR) and augmented reality (AR) make use of facial expression recognition to implement a natural, friendly communication with humans. In this paper an approach for Facial Expression Recognition using Ensemble Learning Technique has been proposed. Ensemble methods use various learning algorithms to obtain good predictive performance that could be obtained from any of the basic learning algorithms alone. In the proposed method, initially the features are extracted from static images using color histograms. This process is done for all images gathered in the training dataset. The ensemble technique is then applied on the featured dataset in order to categorize a given image into one of the six emotions, happy, sad, fear, angry, disgust, and surprise. A satisfactory result has been obtained using static image dataset taken from kaggle and uci machine learning repository

scholarly journals Classification of Facial Expression Recognition using Machine Learning Algorithms

2021 ◽  
Vol 1937 (1) ◽  
pp. 012001
Author(s):  
D Abinaya ◽  
C Priyanka ◽  
M Rocky Stefinjain ◽  
G.K. D Prasanna Venkatesan ◽  
S. Kamalraj
Keyword(s):  
Machine Learning ◽  
Facial Expression ◽  
Facial Expression Recognition ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Expression Recognition

Graph-based dynamic ensemble pruning for facial expression recognition

2019 ◽  
Vol 49 (9) ◽  
pp. 3188-3206 ◽  
Author(s):  
Danyang Li ◽  
Guihua Wen ◽  
Xu Li ◽  
Xianfa Cai
Keyword(s):  
Facial Expression ◽  
Facial Expression Recognition ◽  
Expression Recognition ◽  
Ensemble Pruning
Sign in / Sign up

Export Citation Format

Share Document