This paper presents a template-based algorithm to track and recognize athlete’s actions in an integrated system using only visual information. Conventional template-based action...
In many applications extraction of source signals of interest from observed signals maybe is a more feasible approach than simultaneous separation of all the source signals, since...
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
Background: Nonnegative Matrix Factorization (NMF) is an unsupervised learning technique that has been applied successfully in several fields, including signal processing, face re...
While it is exponentially unlikely that a sparse random graph or hypergraph is connected, with probability 1 − o(1) such a graph has a “giant component” that, given its numbe...