We consider sensor scheduling as the optimal observability problem for partially observable Markov decision processes (POMDP). This model fits to the cases where a Markov process ...
Task reallocation in a multi-robot organization is a process that distributes a decomposed global task to individual robots. This process must be distributed and dynamic because i...
In this work, we propose a new super-resolution algorithm to simultaneously estimate all frames of a video sequence. The new algorithm is based on the Bayesian maximum a posterior...
Abstract. This paper considers the sensor network localization problem using signal strength. Unlike range-based methods signal strength information is stored in a kernel matrix. L...
Hidden Markov Models (HMMs) model sequential data in many fields such as text/speech processing and biosignal analysis. Active learning algorithms learn faster and/or better by cl...