There number of existing methods to transfer information among various disciplines. For multidisciplinary application with disciplines, traditional methods may required model ( 2 n n - interactions. paper presents a unified three-dimensional approach reduces number interactions from ) ( 2 n using a

In this paper, we present a unified approach to the problems of human face detection, segmentation and location. Color and texture are used for searching skinlike regions in the images. Determining whether each region corresponds or not to a face solves the detection problem, and allows a

Using a combination of S-Matrix and perturbative QCD properties in the small xBj regime, we propose a formulation of hard diffraction unifying the partonic (Ingelman-Schlein) Pomeron, Soft Colour Interaction and QCD dipole descriptions. 1

) formulate a unified model that integrates elements across the eight models, and (4) empirically validate the unified model. The eight models reviewed are the theory of reasoned action, the technology acceptance model, the motivational model, the theory of planned behavior, a model combining the technology

, but fail on cold start items. Hybrid schemes attempt to combine these different kinds of information to yield better recommendations across the board. We describe unified Boltzmann machines, which are probabilistic models that combine collaborative and content information in a coherent manner. They encode

underreact in the short run. The underreaction means that the momentum traders can profit by trendchasing. However, if they can only implement simple (i.e., univariate) strategies, their attempts at arbitrage must inevitably lead to overreaction at long horizons. In addition to providing a unified account

through which corruption impacts upon growth, and the conditions under which the direction of the effect takes shape. The findings from our unified framework could rationalise the diverse (and sometimes, apparently conflicting) empirical evidence on the impact of corruption on economic growth offered

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Since the Lucas-Kanade algorithm was proposed in 1981 image alignment has become one of the most widely used techniques in computer vision. Applications range from optical flow, tracking, and layered motion, to mosaic construction, medical image registration, and face coding. Numerous algorithms have been proposed and a variety of extensions have been made to the original formulation. We present an overview of image alignment, describing most of the algorithms in a consistent framework. We concentrate on the inverse compositional algorithm, an efficient algorithm that we recently proposed. We examine which of the extensions to the Lucas-Kanade algorithm can be used with the inverse compositional algorithm without any significant loss of efficiency, and which cannot. In this paper, Part 3 in a series of papers, we cover the extension of image alignment to allow linear appearance variation. We first consider linear appearance variation when the error function is the Euclidean L2 norm. We describe three different algorithms, the simultaneous, project out, and normalization inverse compositional algorithms, and empirically compare them. Afterwards we consider the combination of linear appearance variation with the robust error functions described in Part 2 of this series. We first derive robust versions of the simultaneous and normalization algorithms. Since both of these algorithms are very inefficient, as in Part 2 we derive efficient approximations based on spatial coherence. We end with an empirical evaluation of the robust algorithms.

www.elsevier.com/locate/jalgor Estimating all pairs shortest paths in restricted graph