Frontalization with Adaptive Exponentially-Weighted Average Ensemble Rule for Deep Learning Based Facial Expression Recognition
APCCAS 2018
Pages: 447 - 450
Published: Oct 1, 2018
Abstract
Automatic Facial Expression Recognition (FER) is an important technique in human-computer interfaces and surveillance systems. It classifies the input facial images into one of the basic expressions (e.g., anger, sad, surprise, happy, disgust, fear, and neutral) and has attracted significant attention in pattern recognition and computer vision. In this paper, we proposed an advanced convolutional neural networks based FER system. It applies the...
Paper Details
Title
Frontalization with Adaptive Exponentially-Weighted Average Ensemble Rule for Deep Learning Based Facial Expression Recognition
Published Date
Oct 1, 2018
Pages
447 - 450
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