— Given a wireless sensor network (WSN) whose sensors are randomly and independently distributed in a bounded area following a homogeneous Poisson process with density ρ and eac...
— We study the problem of optimal estimation using quantized innovations, with application to distributed estimation over sensor networks. We show that the state probability dens...
Bayesian motion estimation requires two pdf models: observation model and motion field (prior) model. The optimization process for this method uses sequential approach, e.g. simul...
Stephanus Suryadarma Tandjung, Teddy Surya Gunawan...
A new algorithm is presented for the automatic segmentation and classification of brain tissue from 3D MR scans. It uses discriminative Random Decision Forest classification and ta...
Zhao Yi, Antonio Criminisi, Jamie Shotton, Andr...
Markov random field models provide a robust formulation of low-level vision problems. Among the problems, stereo vision remains the most investigated field. The belief propagation...