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24,105
Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization 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 histogram-based model, the FM has an intrinsic limi ..."
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Cited by 639 (15 self)
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limitation—no spatial information is taken into account. This causes the FM model to work only on well-defined images with low levels of noise; unfortunately, this is often not the the case due to artifacts such as partial volume effect and bias field distortion. Under these conditions, FM model
Gibbs Sampling Methods for Stick-Breaking Priors
"... ... In this paper we present two general types of Gibbs samplers that can be used to fit posteriors of Bayesian hierarchical models based on stick-breaking priors. The first type of Gibbs sampler, referred to as a Polya urn Gibbs sampler, is a generalized version of a widely used Gibbs sampling meth ..."
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Cited by 388 (19 self)
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... In this paper we present two general types of Gibbs samplers that can be used to fit posteriors of Bayesian hierarchical models based on stick-breaking priors. The first type of Gibbs sampler, referred to as a Polya urn Gibbs sampler, is a generalized version of a widely used Gibbs sampling
Social Networks and Labor-Market Outcomes: Towards an Economic Analysis
- American Economic Review
, 1991
"... prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your personal, non-commercial use. Please contact the publisher regarding any further use of this work. Publisher contact information may be obtai ..."
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Cited by 474 (0 self)
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prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your personal, non-commercial use. Please contact the publisher regarding any further use of this work. Publisher contact information may
X-means: Extending K-means with Efficient Estimation of the Number of Clusters
- In Proceedings of the 17th International Conf. on Machine Learning
, 2000
"... Despite its popularity for general clustering, K-means suffers three major shortcomings; it scales poorly computationally, the number of clusters K has to be supplied by the user, and the search is prone to local minima. We propose solutions for the first two problems, and a partial remedy for the t ..."
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Cited by 418 (5 self)
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for the third. Building on prior work for algorithmic acceleration that is not based on approximation, we introduce a new algorithm that efficiently, searches the space of cluster locations and number of clusters to optimize the Bayesian Information Criterion (BIC) or the Akaike Information Criterion (AIC
Real-time simultaneous localisation and mapping with a single camera
, 2003
"... Ego-motion estimation for an agile single camera moving through general, unknown scenes becomes a much more challenging problem when real-time performance is required rather than under the off-line processing conditions under which most successful structure from motion work has been achieved. This t ..."
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Cited by 439 (21 self)
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Ego-motion estimation for an agile single camera moving through general, unknown scenes becomes a much more challenging problem when real-time performance is required rather than under the off-line processing conditions under which most successful structure from motion work has been achieved
Detecting Space-Time Clusters: Prior Work and
, 2005
"... The problem of space-time cluster detection arises in a variety of applications, including disease surveillance and brain imaging. In this work, we briefly review the state of the art in space-time cluster detection, focusing on space-time scan statistics, and we derive a number of new statistics. F ..."
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The problem of space-time cluster detection arises in a variety of applications, including disease surveillance and brain imaging. In this work, we briefly review the state of the art in space-time cluster detection, focusing on space-time scan statistics, and we derive a number of new statistics
SlImmary.-Prior work indicatesitems for the Rathus Assertiveness
"... commonfactor,apprehensionaboutinterpersonalencounters.Employinga revisedmeasureof apprehension,factoranalysisof responsesof 160maleand 144femaleundergraduatesto thesetwo scalesyieldedfive factors:apprehen-sion aboutcommunicatingin groupsand meetings,apprehensionin inter-personalcontexts,apprehension ..."
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commonfactor,apprehensionaboutinterpersonalencounters.Employinga revisedmeasureof apprehension,factoranalysisof responsesof 160maleand 144femaleundergraduatesto thesetwo scalesyieldedfive factors:apprehen-sion aboutcommunicatingin groupsand meetings,apprehensionin inter-personalcontexts,apprehensionin public speakingcontexts,preventingothers fromtakingadvantage,andcontentiousness.Only onecommonfactor,appre-hensionin interpersonalcontexts,wassharedby itemsfrom both scales. Assertivenessrefersto the abilityto makerequests,activelydisagree; expresspersonalrightsandfeelings;initiate,maintain,or disengagefromcon-versations;andto standup for self (3, 6, 17, 19). Attemptsto increase assertivenesshavetypicallyfocusedon shapingboth verbaland nonverbal commu:1ication(1, 2), or alteringmaladaptiveanxietyresponsesin inter-personalconversations(14,21). As such,"Asserrivenessi definedin terms ofcommunication,andthemeasuremenrof assertivenessrelieson communica-tionbehaviors"(15,p. 491). Conceptuallysimilar,apprehensionaboutcorn-
Formal Methods: State of the Art and Future Directions
- ACM Computing Surveys
, 1996
"... ing with credit is permitted. To copy otherwise, to republish, to post on servers, to redistribute to lists, or to use any component of this work in other works, requires prior specific permission and/or a fee. Permissions may be requested from Publications Dept, ACM Inc., 1515 Broadway, New York, N ..."
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Cited by 425 (6 self)
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ing with credit is permitted. To copy otherwise, to republish, to post on servers, to redistribute to lists, or to use any component of this work in other works, requires prior specific permission and/or a fee. Permissions may be requested from Publications Dept, ACM Inc., 1515 Broadway, New York
Distributed Source Coding Using Syndromes (DISCUS): Design and Construction
- IEEE TRANS. INFORM. THEORY
, 1999
"... We address the problem of distributed source coding, i.e. compression of correlated sources that are not co-located and/or cannot communicate with each other to minimize their joint description cost. In this work we tackle the related problem of compressing a source that is correlated with anothe ..."
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Cited by 407 (9 self)
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We address the problem of distributed source coding, i.e. compression of correlated sources that are not co-located and/or cannot communicate with each other to minimize their joint description cost. In this work we tackle the related problem of compressing a source that is correlated
Results 21 - 30
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24,105