Recent Submissions

  • Unconditional maximum likelihood approach for localization of near-field sources in 3-D space 

    Authors:Kabaoǧlu, Nihat; Cirpan, Hakan Ali; Paker, Selçuk
    Publisher and Date:(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 ratios we propose unconditional ML (UML) method for estimating azimuth elevation and range parameters of near-field sources in 3-D space in this paper. Besides these superiorities stability asymptotic unbiasedness asymptotic minimum variance properties are motivated the application ...

  • Support vector regression for surveillance purposes 

    Authors:Özer, Sedat; Cirpan, Hakan Ali; Kabaoǧlu, Nihat
    Publisher and Date:(Springer Verlag, 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 a localizer directly using the regression form of the Support Vector Machines (SVM). The proposed approach considers to use dynamic model together as feature vectors and makes the hyperplane and the support vectors follow the changes in these features. The performance of the ...

  • Support vector machines based target tracking techniques [Destek vektör makineleri tabanlı hedef takip yöntemleri] 

    Authors:Özer, Sedat; Cirpan, Hakan Ali; Kabaoǧlu, Nihat
    Publisher and Date:(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 regression form of the Support Vector Machines (SVM). The proposed approach considers using dynamic model together as feature vectors and makes the hyperplane and the support vectors follow the changes in these features. The performance of the tracker is demostrated in a sensor ...

  • Support vector machines based target tracking techniques 

    Authors:Ozer, Sedat; Cirpan, Hakan Ali; Kabaoǧlu, Nihat
    Publisher and Date:(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 regression form of the Support Vector Machines (SVM). The proposed approach considers using dynamic model together as feature vectors and makes the hyperplane and the support vectors follow the changes in these features. The performance of the tracker is demostrated in a sensor ...

  • Unconditional maximum likelihood approach for localization of near-field sources in 3-D space 

    Authors:Kabaoǧlu, Nihat; Cirpan, Hakan Ali; Paker, Selçuk
    Publisher and Date:(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 ratios we propose unconditional ML (UML) method for estimating azimuth elevation and range parameters of near-field sources in 3-D space in this paper Besides these superiorities stability asymptotic unbiasedness asymptotic minimum variance properties are motivated the application ...

  • Support vector regression for surveillance purposes 

    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 a localizer directly using the regression form of the Support Vector Machines (SVM). The proposed approach considers to use dynamic model together as feature vectors and makes the byperplane and the support vectors follow the changes in these features. The performance of the ...