We consider Bayesian detection/classification of discrete random parameters that are strongly dependent locally due to some deterministic local constraint. Based on the recently ...
Georg Kail, Jean-Yves Tourneret, Franz Hlawatsch, ...
This study presents a boundary-based corner detection method that achieves robust detection for digital objects containing wide angles and various curves using curvature. The bound...
Abstract. In this paper, a method of improving the learning time and convergence rate is proposed to exploit the advantages of artificial neural networks and fuzzy theory to neuron...
Kwang-Baek Kim, Sungshin Kim, Young Hoon Joo, Am S...
A new method of handling the kinematic singularities of serial robotic manipulators is proposed. The idea is to transform the manipulator's workspace W into a desingularized ...
Motivated by combinatorial optimization theory, we propose an algorithmic power allocation method that minimizes the total transmitting power in transmitter diversity systems, prov...
Diomidis S. Michalopoulos, Athanasios S. Lioumpas,...