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We present an EM algorithm for Maximum Likelihood estimation of the location, scale, and skew, and shape parameters of the z distribution, also known as the generalized logistic function (type IV). We use the Barndorff-Nielsen, Kent, and Sørensen representation of the z distribution as a Gaussian location-scale mixture to derive an EM algorithm for estimating the location, scale, skew, and shape parameters...
Cross-docking is a practice in logistics in which shipments are directly moved from an inbound truck into an outbound truck. A recognized problem in this domain is the assignment of trucks to doors in a way that the distance to be traveled between the doors is minimized. This problem is known as the Cross-Dock Door Assignment Problem (CDAP). A lot of research has been conducted regarding this topic...
Generative kernels have emerged in the last years as an effective method for mixing discriminative and generative approaches. In particular, in this paper, we focus on kernels defined on generative models with latent variables (e.g. the states in a Hidden Markov Model). The basic idea underlying these kernels is to compare objects, via a inner product, in a feature space where the dimensions are related...
In this paper, we present a scheme of steganalysis of JPEG images with the use of polynomial fitting and computational intelligence techniques. Based on the Generalized Gaussian Distribution (GGD) model in the quantized DCT coefficients, the errors between the logarithmic domain of the histogram of the DCT coefficients and the polynomial fitting are extracted as features to detect the adulterated...
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