Semisupervised learning of classifiers with application to human-computer interaction
Semisupervised learning of classifiers with application to human-computer interaction
Learning polite behavior with situation models
Proceedings of the 3rd ACM/IEEE international conference on Human robot interaction
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We present a new neural network model for classification of facial expressions based on dimension model that is illumination-invariant and without detectable cues such as a neutral expression. The neural network model on the two-dimensional structure of emotion have improved the limitation of expression recognition based on a small number of discrete categories of emotional expressions, lighting sensitivity, and dependence on cues such as a neutral expression.