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435,173
A Security Architecture for Computational Grids
, 1998
"... Stateoftheart and emerging scientific applications require fast access to large quantities of data and commensurately fast computational resources. Both resources and data are often distributed in a widearea network with components administered locally and independently. Computations may involve ..."
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Cited by 569 (49 self)
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involve hundreds of processes that must be able to acquire resources dynamically and communicate e#ciently. This paper analyzes the unique security requirements of largescale distributed (grid) computing and develops a security policy and a corresponding security architecture. An implementation
LanguageBased InformationFlow Security
 IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
, 2003
"... Current standard security practices do not provide substantial assurance that the endtoend behavior of a computing system satisfies important security policies such as confidentiality. An endtoend confidentiality policy might assert that secret input data cannot be inferred by an attacker throug ..."
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Cited by 821 (57 self)
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Current standard security practices do not provide substantial assurance that the endtoend behavior of a computing system satisfies important security policies such as confidentiality. An endtoend confidentiality policy might assert that secret input data cannot be inferred by an attacker
Detecting faces in images: A survey
 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
, 2002
"... Images containing faces are essential to intelligent visionbased human computer interaction, and research efforts in face processing include face recognition, face tracking, pose estimation, and expression recognition. However, many reported methods assume that the faces in an image or an image se ..."
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Cited by 831 (4 self)
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sequence have been identified and localized. To build fully automated systems that analyze the information contained in face images, robust and efficient face detection algorithms are required. Given a single image, the goal of face detection is to identify all image regions which contain a face regardless
Image registration methods: a survey
 IMAGE AND VISION COMPUTING
, 2003
"... This paper aims to present a review of recent as well as classic image registration methods. Image registration is the process of overlaying images (two or more) of the same scene taken at different times, from different viewpoints, and/or by different sensors. The registration geometrically align t ..."
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Cited by 734 (9 self)
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This paper aims to present a review of recent as well as classic image registration methods. Image registration is the process of overlaying images (two or more) of the same scene taken at different times, from different viewpoints, and/or by different sensors. The registration geometrically align
Investor psychology and security market under and overreactions
 Journal of Finance
, 1998
"... We propose a theory of securities market under and overreactions based on two wellknown psychological biases: investor overconfidence about the precision of private information; and biased selfattribution, which causes asymmetric shifts in investors ’ confidence as a function of their investment ..."
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Cited by 661 (38 self)
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We propose a theory of securities market under and overreactions based on two wellknown psychological biases: investor overconfidence about the precision of private information; and biased selfattribution, which causes asymmetric shifts in investors ’ confidence as a function of their investment
Segmentation of brain MR images through a hidden Markov random field model and the expectationmaximization algorithm
 IEEE TRANSACTIONS ON MEDICAL. IMAGING
, 2001
"... The finite mixture (FM) model is the most commonly used model for statistical segmentation of brain magnetic resonance (MR) images because of its simple mathematical form and the piecewise constant nature of ideal brain MR images. However, being a histogrambased model, the FM has an intrinsic limi ..."
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Cited by 619 (14 self)
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The finite mixture (FM) model is the most commonly used model for statistical segmentation of brain magnetic resonance (MR) images because of its simple mathematical form and the piecewise constant nature of ideal brain MR images. However, being a histogrambased model, the FM has an intrinsic
Image denoising using a scale mixture of Gaussians in the wavelet domain
 IEEE TRANS IMAGE PROCESSING
, 2003
"... We describe a method for removing noise from digital images, based on a statistical model of the coefficients of an overcomplete multiscale oriented basis. Neighborhoods of coefficients at adjacent positions and scales are modeled as the product of two independent random variables: a Gaussian vecto ..."
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Cited by 514 (17 self)
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We describe a method for removing noise from digital images, based on a statistical model of the coefficients of an overcomplete multiscale oriented basis. Neighborhoods of coefficients at adjacent positions and scales are modeled as the product of two independent random variables: a Gaussian
Markov Random Field Models in Computer Vision
, 1994
"... . A variety of computer vision problems can be optimally posed as Bayesian labeling in which the solution of a problem is defined as the maximum a posteriori (MAP) probability estimate of the true labeling. The posterior probability is usually derived from a prior model and a likelihood model. The l ..."
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Cited by 515 (18 self)
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. A variety of computer vision problems can be optimally posed as Bayesian labeling in which the solution of a problem is defined as the maximum a posteriori (MAP) probability estimate of the true labeling. The posterior probability is usually derived from a prior model and a likelihood model
Graphical models, exponential families, and variational inference
, 2008
"... The formalism of probabilistic graphical models provides a unifying framework for capturing complex dependencies among random variables, and building largescale multivariate statistical models. Graphical models have become a focus of research in many statistical, computational and mathematical fiel ..."
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Cited by 800 (26 self)
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The formalism of probabilistic graphical models provides a unifying framework for capturing complex dependencies among random variables, and building largescale multivariate statistical models. Graphical models have become a focus of research in many statistical, computational and mathematical
Modeling Strategic Relationships for Process Reengineering
, 1995
"... Existing models for describing a process (such as a business process or a software development process) tend to focus on the \what " or the \how " of the process. For example, a health insurance claim process would typically be described in terms of a number of steps for assessing and appr ..."
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Cited by 545 (40 self)
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Existing models for describing a process (such as a business process or a software development process) tend to focus on the \what " or the \how " of the process. For example, a health insurance claim process would typically be described in terms of a number of steps for assessing
Results 1  10
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435,173