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Hyperspectral imaging provides new opportunities for improving face recognition accuracy. However, it poses such challenges as difficulty in data acquisition, low signal to noise ratio (SNR), and high dimensionality. In this paper, we propose a novel method for hyperspectral face recognition with good recognition rates. We first reduce noise adaptively from each spectral band and then crop each face...
Inappropriate shocks due to misclassification of supraventricular and ventricular arrhythmias remain a major problem in the care of patients with implantable cardioverter defibrillators (ICDs). The purpose of this study was to investigate the ability of a new covariance-based support vector machine classifier, to distinguish ventricular tachycardia from other rhythms such as supraventricular tachycardia...
Face recognition has received significant attention in the last decades for many potential applications. Recently, the scale invariant feature transform (SIFT) becomes an interesting technique for the task of object recognition. This paper investigated the application of the SIFT approach to the face recognition and proposed a new method based on SIFT and support vector machine (SVM) for the face...
Though millions of images are stored in a large digital image library today, the user can not access or make full use of these image information unless the digital image library is well organized in order to allow efficient browsing, searching and retrieval. Thus, research in image retrieval has been an active discipline since 70's last century. Image retrieval is a typical problem of pattern recognition,...
In this paper, a heart sound analyzer is presented for interpretation of heart sound signals and automated diagnosis of valvular heart disease. The heart sound analyzer includes data acquisition from multiple positions, signal analysis to extract auscultatory features and information, and a knowledge-based program to provide a likely diagnosis. Experiments using clinical data from real patients show...
To provide a robust representation of heart sound signal in an automatic heart disease diagnosis system, a mel-scaled wavelet transform has been developed. It combines the advantages of linear perceptual scale by mel mapping with the suitability of analyzing non-stationary signals by wavelet transform. The heart sound signal is firstly divided into windowing frames. A set of mel-scaled filterbank...
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