Huseyin Cukur

Yildiz Technical University · Department of Electronics and Communications Engineering

To enable feature extraction and reduction in pattern recognition applications, discriminant subspace analysis-based algorithms are used. Among the better-known discriminant subspace techniques for two-pattern recognition is the Fukunaga-Koontz transform (FKT). This technique has been modified to a non-linear version with the aid of kernel machines...

Target detection is a popular research topic in high dimensional data processing area. A great number of detection algorithms have been developed and used in the past three decades, such as: Adaptive Cosine Estimator (ACE), Constrained Energy Minimization (CEM), Spectral Angle Mapper (SAM), Covariance Descriptor (CD) and Matched Filter (MF). Every...

Powerful image editing tools are very common and easy to use these days. This situation may cause some forgeries by adding or removing some information on the digital images. In order to detect these types of forgeries such as region duplication, we present an effective algorithm based on fixed-size block computation and discrete wavelet transform...

Target detection is one of the most important topics for military or civilian applications. In order to address such detection tasks, hyperspectral imaging sensors provide useful images data containing both spatial and spectral information. Target detection has various challenging scenarios for hyperspectral images. To overcome these challenges, co...

The performance of the kernel based techniques depends on the selection of kernel parameters. That’s why; suitable parameter selection is an important problem for many kernel based techniques. This article presents a novel technique to learn the kernel parameters in kernel Fukunaga-Koontz Transform based (KFKT) classifier. The proposed approach det...

Hyperspectral imagery (HSI) is a special form of imaging that is characterized by high spectral resolution with up to hundreds of very narrow and contiguous bands which is ranging from the visible to the infrared region. HSI includes spatial and spectral information, that's why it presents important advantages for anomaly and target detection or cl...

Hyperspectral imagery (HSI) is a special imaging form that is characterized by high spectral resolution with up to hundreds of very narrow and contiguous bands which is ranging from the visible to the infrared region. Since HSI contains more distinctive features than conventional images, its computation cost of processing is very high. That’s why;...

Variable Neighborhood Search (VNS) is one of the methods, called metaheuristic, which are based on searching the solution space quickly to get optimal or approximately optimal solution. This method is based on the systematically neighborhood change in search area and generally used to achieve the optimal solution in a short time in high dimensional...