Many computer vision problems can be formulated in
a Bayesian framework with Markov Random Field (MRF)
or Conditional Random Field (CRF) priors. Usually, the
model assumes that ...
Algorithms for the sparse matrix-vector multiplication (shortly SpM×V ) are important building blocks in solvers of sparse systems of linear equations. Due to matrix sparsity, the...
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Abstract-- Formation control experiments are performed using two robots, each equipped with a camera. When both robots are fully informed of the reference velocity, a decentralized...
A physically based system of interacting polyhedral objects is used to model self-assembly and spontaneous organization of complex structures. The surfaces of the polyhedra in the ...