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A suitable filtering preprocessing is beneficial to hyperspectral image (HSI) classification. In this paper, we design a three-dimensional filtering approach for spectral-spatial HSI classification. The associated three-dimensional filter is the coupling of two kinds of kernels. The former is a Gaussian kernel that collects spatial dependency of spectra, whereas the latter is the derivative of Gaussian...
An important way to improve the performance of naive Bayesian classifiers (NBCs) is to remove or relax the fundamental assumption of independence among the attributes, which usually results in an estimation of joint probability density function (p.d.f.) instead of the estimation of marginal p.d.f. in the NBC design. This paper proposes a non-naive Bayesian classifier (NNBC) in which the independence...
In flexible naïve Bayesian (FNB), the excellent qualities of Gaussian kernel have been demonstrated by the theoretical analyses and experimental comparisons with normal naïve Bayesian (NNB). There are also several types of kernel functions commonly used for probability density estimation, i.e., uniform, triangular, epanechnikov, biweight, triweight and cosine. We call them discontinuous kernels. In...
This paper explores from the security problems about whether fix patches and selective repair of the vulnerabilities, which takes computer vulnerabilities and patches associated into comprehensive consideration. Through selecting some key factors as attributes vectors, I propose the selective vulnerability - patch associated repair model by using support vector machine (SVM) classification method...
Face recognition algorithms mainly differ in how to represent the probe face image using the training data. As the state-of-the-art face recognition algorithm, linear regression computes a reconstruction matrix from the images of each subject and then approximates the probe face image using the reconstruction matrix. However, the performance of this linear algorithm is limited due to the nonlinear...
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