Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghah...
In a variety of disciplines such as social sciences, psychology, medicine and economics, the recorded data are considered to be noisy measurements of latent variables connected by...
This paper introduces a novel deformable model for face mapping and its application to automatic person identification. While most face recognition techniques directly model the f...
In this paper, we focus on the use of three different techniques that support automatic derivation of video content from raw video data, namely, a spatio-temporal rule-based metho...
This paper presents an efficient method to integrate various spatial-temporal constraints to regularize the contour tracking. The global shape of the contour is represented in a p...