Matches in SemOpenAlex for { <https://semopenalex.org/work/W1522995767> ?p ?o ?g. }
Showing items 1 to 93 of
93
with 100 items per page.
- W1522995767 endingPage "89" @default.
- W1522995767 startingPage "74" @default.
- W1522995767 abstract "AbstractThe goal of segmentation is to partition an image into a finite set of regions, homogeneous in some (e.g., statistical) sense, thus being an intrinsically discrete problem. Bayesian approaches to segmentation use priors to impose spatial coherence; the discrete nature of segmentation demands priors defined on discrete-valued fields, thus leading to difficult combinatorial problems.This paper presents a formulation which allows using continuous priors, namely Gaussian fields, for image segmentation. Our approach completely avoids the combinatorial nature of standard Bayesian approaches to segmentation. Moreover, it’s completely general, i.e., it can be used in supervised, unsupervised, or semi-supervised modes, with any probabilistic observation model (intensity, multispectral, or texture features).To use continuous priors for image segmentation, we adopt a formulation which is common in Bayesian machine learning: introduction of hidden fields to which the region labels are probabilistically related. Since these hidden fields are real-valued, we can adopt any type of spatial prior for continuous-valued fields, such as Gaussian priors. We show how, under this model, Bayesian MAP segmentation is carried out by a (generalized) EM algorithm. Experiments on synthetic and real data shows that the proposed approach performs very well at a low computational cost.KeywordsImage SegmentationObservation ModelGaussian PriorPosterior Class ProbabilityIEEE CVPRThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves." @default.
- W1522995767 created "2016-06-24" @default.
- W1522995767 creator A5026826555 @default.
- W1522995767 date "2005-01-01" @default.
- W1522995767 modified "2023-09-23" @default.
- W1522995767 title "Bayesian Image Segmentation Using Gaussian Field Priors" @default.
- W1522995767 cites W1480376833 @default.
- W1522995767 cites W1522547150 @default.
- W1522995767 cites W1570612738 @default.
- W1522995767 cites W1989222601 @default.
- W1522995767 cites W2005245664 @default.
- W1522995767 cites W2015245929 @default.
- W1522995767 cites W2024109869 @default.
- W1522995767 cites W2044465660 @default.
- W1522995767 cites W2049694710 @default.
- W1522995767 cites W2065301447 @default.
- W1522995767 cites W2098152234 @default.
- W1522995767 cites W2098347925 @default.
- W1522995767 cites W2099915247 @default.
- W1522995767 cites W2100860054 @default.
- W1522995767 cites W2104094303 @default.
- W1522995767 cites W2117063635 @default.
- W1522995767 cites W2119823327 @default.
- W1522995767 cites W2121947440 @default.
- W1522995767 cites W2123282994 @default.
- W1522995767 cites W2132603077 @default.
- W1522995767 cites W2143516773 @default.
- W1522995767 cites W2150579376 @default.
- W1522995767 cites W2160167256 @default.
- W1522995767 cites W2163025304 @default.
- W1522995767 cites W2167837909 @default.
- W1522995767 cites W2171612090 @default.
- W1522995767 cites W4232632925 @default.
- W1522995767 cites W4253515568 @default.
- W1522995767 doi "https://doi.org/10.1007/11585978_6" @default.
- W1522995767 hasPublicationYear "2005" @default.
- W1522995767 type Work @default.
- W1522995767 sameAs 1522995767 @default.
- W1522995767 citedByCount "21" @default.
- W1522995767 countsByYear W15229957672013 @default.
- W1522995767 countsByYear W15229957672014 @default.
- W1522995767 countsByYear W15229957672015 @default.
- W1522995767 countsByYear W15229957672016 @default.
- W1522995767 countsByYear W15229957672017 @default.
- W1522995767 crossrefType "book-chapter" @default.
- W1522995767 hasAuthorship W1522995767A5026826555 @default.
- W1522995767 hasBestOaLocation W15229957672 @default.
- W1522995767 hasConcept C107673813 @default.
- W1522995767 hasConcept C121332964 @default.
- W1522995767 hasConcept C124504099 @default.
- W1522995767 hasConcept C153180895 @default.
- W1522995767 hasConcept C154945302 @default.
- W1522995767 hasConcept C163716315 @default.
- W1522995767 hasConcept C177769412 @default.
- W1522995767 hasConcept C25694479 @default.
- W1522995767 hasConcept C41008148 @default.
- W1522995767 hasConcept C61224824 @default.
- W1522995767 hasConcept C62520636 @default.
- W1522995767 hasConcept C65885262 @default.
- W1522995767 hasConcept C89600930 @default.
- W1522995767 hasConceptScore W1522995767C107673813 @default.
- W1522995767 hasConceptScore W1522995767C121332964 @default.
- W1522995767 hasConceptScore W1522995767C124504099 @default.
- W1522995767 hasConceptScore W1522995767C153180895 @default.
- W1522995767 hasConceptScore W1522995767C154945302 @default.
- W1522995767 hasConceptScore W1522995767C163716315 @default.
- W1522995767 hasConceptScore W1522995767C177769412 @default.
- W1522995767 hasConceptScore W1522995767C25694479 @default.
- W1522995767 hasConceptScore W1522995767C41008148 @default.
- W1522995767 hasConceptScore W1522995767C61224824 @default.
- W1522995767 hasConceptScore W1522995767C62520636 @default.
- W1522995767 hasConceptScore W1522995767C65885262 @default.
- W1522995767 hasConceptScore W1522995767C89600930 @default.
- W1522995767 hasLocation W15229957671 @default.
- W1522995767 hasLocation W15229957672 @default.
- W1522995767 hasOpenAccess W1522995767 @default.
- W1522995767 hasPrimaryLocation W15229957671 @default.
- W1522995767 hasRelatedWork W1507266234 @default.
- W1522995767 hasRelatedWork W1977295039 @default.
- W1522995767 hasRelatedWork W2005476934 @default.
- W1522995767 hasRelatedWork W2045775567 @default.
- W1522995767 hasRelatedWork W2108678662 @default.
- W1522995767 hasRelatedWork W2143813385 @default.
- W1522995767 hasRelatedWork W2152768474 @default.
- W1522995767 hasRelatedWork W2163381555 @default.
- W1522995767 hasRelatedWork W2169670048 @default.
- W1522995767 hasRelatedWork W2269938779 @default.
- W1522995767 isParatext "false" @default.
- W1522995767 isRetracted "false" @default.
- W1522995767 magId "1522995767" @default.
- W1522995767 workType "book-chapter" @default.