Abstract. Bayesian inference provides a powerful framework to optimally integrate statistically learned prior knowledge into numerous computer vision algorithms. While the Bayesian...
This paper considers the problems of feature variation and concept uncertainty in typical learning-based video semantic classification schemes. We proposed a new online semantic c...
Abstract. The paper focuses on the efficiency of the hybrid evolutionary algorithm (HEA) for solving the global optimization problem arising in electronic imaging. The particular v...
Evolutionary algorithms (EAs) have been applied with success to many numerical and combinatorial optimization problems in recent years. However, they often lose their effectivenes...
This paper addresses the evolution of control strategies for a collective: a set of entities that collectively strives to maximize a global evaluation function that rates the perf...