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Automatic classification of Human Epithelial Type-2 (HEp-2) specimen patterns is an important yet challenging problem in medical image analysis. Most prior works have primarily focused on cells images classification problem which is one of the early essential steps in the system pipeline, while less attention has been paid to the classification of whole-specimen ones. In this work, a specimen pattern...
Automatic classification of Human Epithelial Type-2 (HEp-2) cells staining patterns is a challenging and important problem in the field of medical image analysis. This paper proposed an efficient framework to address the HEp-2 cell image classification problem based on wavelet scattering network and Random Forest. The wavelet scattering network computes rotation-invariant wavelet coefficients as representations...
Accurate grid resources prediction is crucial for a grid scheduler. In this study, support vector regression (SVR), which is an effective regression algorithm, is applied to grid resource prediction. In order to obtain better prediction performance, SVR's parameters must be selected carefully. Therefore, a particle swarm optimization-based SVR (PSO-SVR) model, in which PSO is used to determine free...
As a supervised learning algorithm, the standard Gaussian processes has the excellent performance of classification. In this paper, we present a semi-supervised algorithm to learning a Gaussian process classifier, which incorporating a graph-based construction of semi-supervised kernels in the presence of labeled and unlabeled data, and expanding the standard Gaussian processes algorithm into the...
In this paper, a novel harmonic retrieval scheme is proposed, which is based on least squares support vector machines (LS-SVM). We consider harmonic signals corrupted by additive noises. The harmonic model is expended by wavelet series, and the corresponding parameters are estimated by weighted LS-SVM approach. Wavelet kernel is adopted to enhance the resolution. Simulations performed on synthetic...
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