2018
DOI: 10.5815/ijigsp.2018.09.04
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Pattern Averaging Technique for Facial Expression Recognition Using Support Vector Machines

Abstract: Facial expression is one of the nonverbal communication methods of identifying an emotional state of a human being. Due to its crucial importance in Human-Robot interaction, facial expression recognition (FER) is in the limelight of recent research activities. Most of the studies consider the whole expression images in their analysis, and it has several has several drawbacks concerning illumination, orientation, texture, zoom level, time and space complexity. In this paper, a novel feature extraction technique… Show more

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Cited by 5 publications
(1 citation statement)
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“…Generative Adversarial Networks, Convolution neural networks, Deep Autoencoder (DAE), Recurrent Neural Networks (RNN), and Deep belief networks, are used for feature learning. For classification, CNN is used that regulate the error by adding a loss layer to the end of the network [4].…”
Section: Literature Reviewmentioning
confidence: 99%
“…Generative Adversarial Networks, Convolution neural networks, Deep Autoencoder (DAE), Recurrent Neural Networks (RNN), and Deep belief networks, are used for feature learning. For classification, CNN is used that regulate the error by adding a loss layer to the end of the network [4].…”
Section: Literature Reviewmentioning
confidence: 99%