Toplam kayıt 5, listelenen: 1-5

    • Fast Target Detection in Radar Images Using Rayleigh Mixtures And Summed Area Tables 

      Nar, Fatih; Okman, Osman Erman; Ozgur, Atilla; Cetin, Mujdat (2018)
      As the first step of automatic image interpretation systems, automatic detection of targets should be accurate and fast. For Synthetic Aperture Radar (SAR) images, Constant False Alarm Rate (CFAR) is the most popular ...
    • Parallelization of Sparsity-driven Change Detection Method 

      Ozgur, Atilla; Saran, Ayse Nurdan; Nar, Fatih (2017)
      In this study, Sparsity-driven Change Detection (SDCD) method, which has been proposed for detecting changes in multitemporal synthetic aperture radar (SAR) images, is parallelized to reduce the execution time. Parallelization ...
    • RmSAT-CFAR: Fast and accurate target detection in radar images 

      Nar, Fatih; Okman, Osman Erman; Ozgur, Atilla; Cetin, Mujdat (2018)
      As the first step of automatic image interpretation systems, automatic detection of the targets should be accurate and fast. Constant False Alarm Rate (CFAR) is the most popular target detection framework for Synthetic ...
    • Sparsity-Driven Change Detection in Multitemporal SAR Images 

      Nar, Fatih; Ozgur, Atilla; Saran, Ayse Nurdan (2016)
      In this letter, a method for detecting changes in multitemporal synthetic aperture radar (SAR) images by minimizing a novel cost function is proposed. This cost function is constructed with log-ratio-based data fidelity ...
    • Sparsity-driven weighted ensemble classifier 

      Erdem, Hamit; Ozgur, Atilla; Nar, Fatih (2018)
      In this study, a novel sparsity-driven weighted ensemble classifier (SDWEC) that improves classification accuracy and minimizes the number of classifiers is proposed. Using pre-trained classifiers, an ensemble in which ...