Abstract-The scale-space technique introduced by Witkin involves generating coarser resolution images by convolving the original image with a Gaussian kernel. This approach has a major drawback: it is difficult to obtain accurately the locations of the “semantically mean-ingful ” edges at coarse

wide variety of lighting conditions can be approximated accurately by a low-dimensional linear subspace, explaining prior empirical results. We also provide a simple analytic characterization of this linear space. We obtain these results by representing lighting using spherical harmonics and describing

that the FM model is a degenerate version of the HMRF model. The advantage of the HMRF model derives from the way in which the spatial information is encoded through the mutual influences of neighboring sites. Although MRF modeling has been employed in MR image segmentation by other researchers, most reported

Many prominent theorists have argued that accurate perceptions of the self, the world, and the future are essential for mental health. Yet considerable research evidence suggests that overly positive selfevaluations, exaggerated perceptions of control or mastery, and unrealistic optimism

steady states it seems reasonable to try to find a way to com bine the two values. The simplest thing to do is to average them. Unfortunately, this gave very poor re sults, since the correct posteriors do not usually lie in the midpoint of the interval ( cf. 2More precisely, we found that with a

19. Plantinga LC, Fink NE, Jaar BG et al. Attainment of clinical perfor-mance targets and improvement in clinical outcomes and resource use in hemodialysis care: a prospective cohort study. BMC Health Serv

Abstract Effective engineering of the Internet is predicated upon a detailed understanding of issues such as the large-scale structure of its underlying physical topology, the manner in which it evolves over time, and the way in which its constituent components contribute to its overall function

accurate. We propose a new way of measuring the smoothness of a numerical solution, emulating the idea of minimizing the total variation of the approximation, which results in a 5th order WENO scheme for the case r = 3, instead of the 4th order with the original smoothness measurement by Liu et al. This 5

One of the most promising developments in holding schools accountable is the use of growth models, which are systems that measure student progress from one point in time to another. NEA is working with state affiliates to redesign accountability systems that assess student learning in a fair and reliable manner. Our goal is improved teaching and learning for every student. —NEA President Dennis Van Roekel Growth models, used in education accountability systems, assess student performance by comparing their growth on a concept, knowledge, or skill between two or more points in time. Teachers commonly use a form of this model when they administer pre-tests and post-tests in their classrooms. Growth

Particle filters (PFs) are powerful sampling-based inference/learning algorithms for dynamic Bayesian networks (DBNs). They allow us to treat, in a principled way, any type of probability distribution, nonlinearity and non-stationarity. They have appeared in several fields under such names