Browsing Yüksekokullar by Type "conferenceObject"
Now showing items 1-7 of 7
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Mobile Application Development for the Estimation of Recurrence in Post-Operative Kidney Cancer Cases
(IEEE, 2018)In this paper a post-operative recurrence estimation tool called Sorbellini's nomogram for the kidney cancer patients showing no metastates is introduced and a novel application for mobile devices based on this model is ... -
Near field parameter estimation of moving sources with recursive expectation maximization algorithm
(IEEE, 2006)In this paper maximum likelihood (ML) estimator is proposed for the joint estimation of the direction of arrival (DOA) and range parameters of moving sources in the near-field of the antenna array. ML estimation algorithm ... -
Near field parameter estimation of moving sources with recursive expectation maximization algorithm [Yinelemeli beklenti/en büyükleme algoritması ile hareketli kaynakların yakın-alan parametrelerinin kestirimi]
(2006)In this paper maximum likelihood (ML) estimator is proposed for the joint estimation of the direction of arrival (DOA) and range parameters of moving sources in the near-field of the antenna array. ML estimation algorithm ... -
Support vector machines based target tracking techniques
(IEEE, 2006)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 machines based target tracking techniques [Destek vektör makineleri tabanlı hedef takip yöntemleri]
(2006)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 ... -
Unconditional maximum likelihood approach for localization of near-field sources in 3-D space
(IEEE, 2004)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 ...