: Integrating the outputs of multiple classifiers via combiners or meta-learners has led to substantial improvements in several difficult pattern recognition problems. In this arti...
Abstract—Diffusions are useful for image processing and computer vision because they provide a convenient way of smoothing noisy data, analyzing images at multiple scales, and en...
This paper applies time-varying autoregressive (TVAR) models with stochastically evolving parameters to the problem of speech modeling and enhancement. The stochastic evolution mod...
Parallel volume rendering is one of the most efficient techniques to achieve real time visualization of large datasets by distributing the data and the rendering process over a c...
We investigate how to discover all common visual patterns within two sets of feature points. Common visual patterns generally share similar local features as well as similar spati...