A novel approach to computer vision is outlined, involving the use of imprecise probabilities to connect a deep learning based hierarchical vision system with both local feature de...
Powerful statistical models that can be learned efficiently from large amounts of data are currently revolutionizing computer vision. These models possess a rich internal structur...
We present a random field based model for stereo vision with explicit occlusion labeling in a probabilistic framework. The model employs non-parametric cost functions that can be ...
Abstract. Most cognitive studies of language acquisition in both natural systems and artificial systems have focused on the role of purely linguistic information as the central co...
Abstract. Successful multi-target tracking requires locating the targets and labeling their identities. This mission becomes significantly more challenging when many targets freque...