Bayesian networks provide a modeling language and associated inference algorithm for stochastic domains. They have been successfully applied in a variety of medium-scale applicati...
This paper presents a novel method to determine the complete velocity vector of a moving target using a single Synthetic Aperture Radar (SAR) sensor. The method exploits the struc...
Background: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distribut...
— The Bayesian occupancy filter (BOF) [1] has achieved promising results in the object tracking applications. This paper presents a new development of BOF which inherits origina...
Cheng Chen, Christopher Tay, Christian Laugier, Ka...
We present a new approach for building reconstruction from a single Digital Elevation Model (DEM). It treats buildings as an assemblage of simple urban structures extracted from a...