This paper presents a local appearance feature fusion for automatic emotion recognition using Convolutional Neural Network (CNN). The CNN has been known to be a powerful texture feature for facial expression recognition. However, only few approaches utilize the relationship among neighborhood pixels itself. First, CNN is obtained based on two closest vertical and/or horizontal neighborhood pixel relationships. The proposed work is also extended to efficiently handle a large amount of unlabeled data using supervised classification algorithm using modified CNN. At the last stage, ensemble classifiers are trained with a small percentage labeled data and based on the trained model, rest of the unlabeled data is assigned with pseudo-labels.
P Senthilkumar
Kalasalingam Academy of Research and Education, India
Cloud Computing, Reliability Assessment, Trust Proof, Personal Opinion, Internet of Things | Published By :
ICTACT
Published In :
ICTACT Journal on Data Science and Machine Learning
( Volume: 1 , Issue: 2 )
Date of Publication :
March 2020
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