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USTC-AC

Chongliang Wu

Capturing global spatial patterns for distinguishing posed and spontaneous expressions
Emotion Recognition from EEG Signals Enhanced by User's Profile
Facial Expression Recognition with Deep two-view Support Vector Machine
Implicit hybrid video emotion tagging by integrating video content and users' multiple physiological responses
Posed and Spontaneous Expression Recognition Through Restricted Boltzmann Machine
Multi-instance Hidden Markov Model for facial expression recognition
Posed and spontaneous expression recognition through modeling their spatial patterns
Posed and spontaneous facial expression differentiation using deep Boltzmann machines
Capture expression-dependent AU relations for expression recognition
Facial Action Unit recognition by relation modeling from both qualitative knowledge and quantitative data

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