Dynamic probabilistic networks are a compact representation of complex stochastic processes. In this paper we examine how to learn the structure of a DPN from data. We extend stru...
We present an optimization method and algorithm designed for three objectives: physical data independence, semantic optimization, and generalized tableau minimization. The method ...
In this paper, the hardware implementation of a vector median like filter is proposed. Firstly, the extension of median filtering to the case of multicomponent images is addressed...
Jocelyn Chanussot, Michel Paindavoine, Patrick Lam...
Recent research has shown that one can use Distributed Hash Tables (DHTs) to build scalable, robust and efficient applications. One question that is often left unanswered is that ...
This paper presents a novel algorithm for online structure and motion estimation. The algorithm works for general camera models and minimizes object space error, it does not rely ...