Comments on "Application of the Conditional Population-Mixture Model to Image Segmentation"

No abstract is available for this paper.

• Publication year

  1984

• Venue

  IEEE Transactions on Pattern Analysis and Machine Intelligence

• Publication date

  1984-05-01

• Fields of study

  Mathematics, Computer Science

• Identifiers
  DOI 10.1109/TPAMI.1984.4767581
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Mixture densities, maximum likelihood, and the EM algorithm

  1984cited by this paper
• On Jointly Estimating Parameters and Missing Data by Maximizing the Complete-Data Likelihood

  1983cited by this paper
• On Segmentation of Digital Images Using Spatial and Contextual Information via a Two-Dimensional Markov Model.

  1983cited by this paper
• Statistical Modelling of Data on Teaching Styles

  1981cited by this paper
• Clustering criteria and multivariate normal mixtures

  1981cited by this paper
• Likelihood of a model and information criteria

  1981cited by this paper
• Asymptotic behaviour of classification maximum likelihood estimates

  1978cited by this paper
• A quasi-Bayes unsupervised learning procedure for priors (Corresp.)

  1977cited by this paper
• Population mixture models and clustering algorithms

  1977cited by this paper
• 389: Separating Mixtures of Normal Distributions

  1975cited by this paper
• A new look at the statistical model identification

  1974cited by this paper
• On decision-directed estimation and stochastic approximation (Corresp.)

  1972cited by this paper
• Clustering methods based on likelihood ratio criteria.

  1971cited by this paper

• Computational Bayesian Analysis of Hidden

  2016cites this paper
• Parallel sequential Monte Carlo samplers and estimation of the number of states in a Hidden Markov Model

  2014cites this paper
• Bivariate Markov Processes and Their Estimation

  2013cites this paper
• The adjusted Viterbi training for hidden

  2008influential citation
• Adjusted Viterbi training for hidden Markov models

  2007cites this paper
• On Adjusted Viterbi Training

  2007cites this paper
• Speaker classification using composite hypothesis testing and list decoding

  2005cites this paper
• EM procedures using mean field-like approximations for Markov model-based image segmentation

  2003influential citation
• A unifying framework for partial volume segmentation of brain MR images

  2003cites this paper
• Stochastic Model Based Image Analysis

  2002cites this paper
• Hidden Markov processes

  2002cites this paper
• Quantitative analysis of signal abnormalities in MR imaging for multiple sclerosis and creutzfeldt-jakob disease

  2001cites this paper
• A Statistical Framework for Partial Volume Segmentation

  2001cites this paper
• Image Analysis and Graphics for Multimedia Presentation

  2001cites this paper
• Quantitative Analysis of Signal Abnormalities in MR Imaging

  2001cites this paper
• Testing for Acceptance–Rejection

  1999cites this paper
• Data mapping by probabilistic modular networks and information-theoretic criteria

  1998influential citation
• Computational Bayesian Analysis of Hidden Markov Models

  1998cites this paper
• Quantification and segmentation of brain tissues from MR images: a probabilistic neural network approach

  1998influential citation
• Computational Bayesian Analysis of Hidden Markov Mesh Models

  1997cites this paper
• Hidden Markov Models and Animal Behaviour

  1995cites this paper
• Neural Networks: A Review from a Statistical Perspective

  1994cites this paper
• Parameter Estimation for Markov Modulated Poisson Processes

  1994cites this paper
• Tissue classification and segmentation of MR images

  1993cites this paper
• Statistical approach to X-ray CT imaging and its applications in image analysis. II. A new stochastic model-based image segmentation technique for X-ray CT image

  1992influential citation
• Estimation of parameters in hidden Markov models

  1991cites this paper
• Some recent research in the analysis of mixture distributions

  1990cites this paper
• Statistically Based Unsupervised Hierarchical Image Segmentation Algorithm With A Blurring Corrector

  1989cites this paper
• Optimality of reassignment rules in dynamic clustering

  1988cites this paper
• Another interpretation of the EM algorithm for mixture distributions

  1986cites this paper
• On the Statistical Analysis of Dirty Pictures

  1986cites this paper
• Predictive Likelihood Inference with Applications

  1986cites this paper
• Picture processing: 1984

  1985cites this paper
• Optic flow segmentation as an ill-posed and maximum likelihood problem

  1985cites this paper