The goal of this communication is to present a weighted likelihood discriminant for minimum error shape classification. Different from traditional Maximum Likelihood (ML) methods...
This paper proposes a simple yet new and effective framework by combining generative model and discriminative model for natural scene categorization. A state-of-the-art approach f...
In this study, we propose increasing discriminative power on the maximum a posteriori (MAP)-based mapping function estimation for acoustic model adaptation. Based on the effective...
During face-to-face conversation, people naturally integrate speech, gestures and higher level language interpretations to predict the right time to start talking or to give backc...
This paper proposed an approach of human behavior modeling based on Discriminative Random Fields. In this model, by introducing the hidden behavior feature functions and time wind...