In this paper, we propose a Bayesian Pursuit algorithm for sparse representation. It uses both the simplicity of the pursuit algorithms and optimal Bayesian framework to determine...
Hadi Zayyani, Massoud Babaie-Zadeh, Christian Jutt...
— This paper presents a new updating algorithm to reduce the complexity of computing an observability index for kinematic calibration of robots. An active calibration algorithm i...
Ongoing research has established a new methodology for using genetic algorithms [2] to evolve forward and inverse transforms that significantly reduce quantization error in recons...
A straightforward and efficient way to discover clustering tendencies in data using a recently proposed Maximum Variance Clustering algorithm is proposed. The approach shares the ...
A new approach to characterizing the performance of point-correspondence algorithms is presented. Instead of relying on any \ground truth', it uses the self-consistency of th...