Now showing items 1-4 of 4
Support vector machines based target tracking techniques
This paper addresses the problem of aplying powerful statistical pattern classification algorithms based on kernels to target tracking. Rather than directly adapting a recognizer we develop a localizer directly using the ...
Support vector regression for surveillance purposes
(Springer-Verlag Berlin, 2006)
This paper addresses the problem of applying powerful statistical pattern classification algorithm based on kernel functions to target tracking on surveillance systems. Rather than directly adapting a recognizer we develop ...
EM based Stochastic maximum likelihood approach for localization of near-field sources in 3-D
(Walter De Gruyter Gmbh, 2004)
The goal of this paper is to estimate the locations of unknown sources in 3-D space from the data collected by a 2-D rectangular array. Various studies employing different estimation methods under near-field and far-field ...
Unconditional maximum likelihood approach for localization of near-field sources in 3-D space
Since maximum likelihood (ML) approaches have better resolution performance than the conventional localization methods in the presence of less number and highly correlated source signal samples and low signal to noise ...