Adaptive Channel Balancing Algorithm Based on 2-D Gaussian Kernel Function

2021 ◽  
pp. 1-5
Author(s):  
Leilei Xu ◽  
Peng Liu ◽  
Bingji Zhao ◽  
Qingjun Zhang ◽  
Yaqiu Jin
Keyword(s):  
Kernel Function ◽  
Gaussian Kernel ◽  
Gaussian Kernel Function

scholarly journals Adaptive Image Mismatch Removal With Vector Field Interpolation Based on Improved Regularization and Gaussian Kernel Function

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 55599-55613 ◽  
Author(s):  
Yongjun Zhang ◽  
Xunwei Xie ◽  
Xiang Wang ◽  
Yansheng Li ◽  
Xiao Ling
Keyword(s):  
Vector Field ◽  
Kernel Function ◽  
Gaussian Kernel ◽  
Gaussian Kernel Function

scholarly journals Weighted Feature Gaussian Kernel SVM for Emotion Recognition

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Wei Wei ◽  
Qingxuan Jia
Keyword(s):  
Facial Expression ◽  
Emotion Recognition ◽  
Kernel Function ◽  
Recognition Rate ◽  
Gaussian Kernel ◽  
Support Vector ◽  
The Past ◽  
Gaussian Kernel Function ◽  
Feature Based ◽  
Novel Method

Emotion recognition with weighted feature based on facial expression is a challenging research topic and has attracted great attention in the past few years. This paper presents a novel method, utilizing subregion recognition rate to weight kernel function. First, we divide the facial expression image into some uniform subregions and calculate corresponding recognition rate and weight. Then, we get a weighted feature Gaussian kernel function and construct a classifier based on Support Vector Machine (SVM). At last, the experimental results suggest that the approach based on weighted feature Gaussian kernel function has good performance on the correct rate in emotion recognition. The experiments on the extended Cohn-Kanade (CK+) dataset show that our method has achieved encouraging recognition results compared to the state-of-the-art methods.

Sign in / Sign up

Export Citation Format

Share Document