Symbolic AI systems typically have difficulty reasoning about motion in continuous environments, such as determining whether a cornering car will clear a close obstacle. Bimodal s...
Abstract— We consider the linear minimum meansquared error (LMMSE) estimation of a random vector of interest from its fusion frame measurements in presence noise and subspace era...
Ali Pezeshki, Gitta Kutyniok, A. Robert Calderbank
The use of good random numbers is essential to the integrity of many mission-critical systems. However, when such systems are replicated for Byzantine fault tolerance, a serious i...
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 ...
This paper proposes a new concept in hierarchical representations that exploits features of different granularity and specificity coming from all layers of the hierarchy. The conc...