Intelligent classification of fetal doppler blood velocity wavefrom abnormalities using wavelet transform and vector quantization algorithm

Izzetoğlu, Kurtuluş


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Automatic Bayesian segmentation of human facial tissue using 3D MR-CT fusion by incorporating models of measurement blurring, noise and partial volume
Şener, Emre; Kanoğlu, Utku; Mumcuoğlu, Ünal Erkan; Department of Engineering Sciences (2012)
Segmentation of human head on medical images is an important process in a wide array of applications such as diagnosis, facial surgery planning, prosthesis design, and forensic identification. In this study, a new Bayesian method for segmentation of facial tissues is presented. Segmentation classes include muscle, bone, fat, air and skin. The method incorporates a model to account for image blurring during data acquisition, a prior helping to reduce noise as well as a partial volume model. Regularization ba...
Efficient detection and tracking of salient regions for visual processing on mobile platforms
Serhat, Gülhan; Saranlı, Afşar; Department of Electrical and Electronics Engineering (2009)
Visual Attention is an interesting concept that constantly widens its application areas in the field of image processing and computer vision. The main idea of visual attention is to find the locations on the image that are visually attractive. In this thesis, the visually attractive regions are extracted and tracked in video sequences coming from the vision systems of mobile platforms. First, the salient regions are extracted in each frame and a feature vector is constructed for each one. Then Scale Invaria...
Taşeli, Hasan (Wiley, 1993-01-01)
The eigenvalues of the Schrodinger equation with a polynomial potential are calculated accurately by means of the Rayleigh-Ritz variational method and a basis set of functions satisfying Dirichlet boundary conditions. The method is applied to the well potentials having one, two, and three minima. It is shown, in the entire range of coupling constants, that the basis set of trigonometric functions has the capability of yielding the energy spectra of unbounded problems without any loss of convergence providin...
Automated accurate emotion classification using Clefia pattern-based features with EEG signals
Doğan, Abdullah; Barua, Prabal Datta; BAYĞIN, MEHMET; Tuncer, Turker; DOĞAN, ŞENGÜL; YAMAN, ORHAN; Doğru, Ali Hikmet; Acharya, Rajendra U. (2022-11-01)
Background: The electroencephalogram (EEG) emotion classification/recognition is one of the popular issues for advanced signal classification. However, it is difficult to manually screen the EEG signals as they are highly nonlinear and non-stationary. Methods: This paper introduces a novel nonlinear and multileveled features-based automatic EEG emotion classification method. Our presented EEG classification model uses feature vector creation deploying an S-Box-based local pattern with a decomposition (tunab...
Citation Formats
K. Izzetoğlu, “Intelligent classification of fetal doppler blood velocity wavefrom abnormalities using wavelet transform and vector quantization algorithm,” Middle East Technical University, 1995.