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Energy Minimization Methods in Computer Vision and Pattern Recognition : Second International Workshop, EMMCVPR'99, York, UK, July 26-29, 1999, Proceedings - Alois Wenig
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Energy Minimization Methods in Computer Vision and Pattern Recognition - Edwin R. Hancock; Marcello Pelillo
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EAN (ISBN-13): 9783540484325
Editeur: Springer Science+Business Media

Livre dans la base de données depuis 2017-05-10T01:39:21+02:00 (Paris)
Page de détail modifiée en dernier sur 2023-06-14T19:18:44+02:00 (Paris)
ISBN/EAN: 9783540484325

ISBN - Autres types d'écriture:
978-3-540-48432-5
Autres types d'écriture et termes associés:
Titre du livre: pattern recognition


Données de l'éditeur

Auteur: Edwin R. Hancock; Marcello Pelillo
Titre: Lecture Notes in Computer Science; Energy Minimization Methods in Computer Vision and Pattern Recognition - Second International Workshop, EMMCVPR'99, York, UK, July 26-29, 1999, Proceedings
Editeur: Springer; Springer Berlin
338 Pages
Date de parution: 2003-07-31
Berlin; Heidelberg; DE
Langue: Anglais
53,49 € (DE)
55,00 € (AT)
59,00 CHF (CH)
Available
X, 338 p.

EA; E107; eBook; Nonbooks, PBS / Informatik, EDV/Anwendungs-Software; Mustererkennung; Verstehen; 3D; Animation; Biomathematics; Computer Vision; Energy Minimization; Image segmentation; Markov Random Field; Markov Random Fields; Pattern Recognition; Shading; algorithm; algorithms; genetic algorithms; image analysis; image restoration; C; Automated Pattern Recognition; Computer Vision; Computer Science Logic and Foundations of Programming; Complex Systems; Mathematical and Computational Biology; Theoretical, Mathematical and Computational Physics; Computer Science; Maschinelles Sehen, Bildverstehen; Theoretische Informatik; Kybernetik und Systemtheorie; DV-gestützte Biologie/Bioinformatik; Mathematische Physik; BC

Shape.- A Hamiltonian Approach to the Eikonal Equation.- Topographic Surface Structure from 2D Images Using Shape-from-Shading.- Harmonic Shape Images: A Representation for 3D Free-Form Surfaces Based on Energy Minimization.- Deformation Energy for Size Functions.- Minimum Description Length.- On Fitting Mixture Models.- Bayesian Models for Finding and Grouping Junctions.- Markov Random Fields.- Semi-iterative Inferences with Hierarchical Energy-Based Models for Image Analysis.- Metropolis vs Kawasaki Dynamic for Image Segmentation Based on Gibbs Models.- Hyperparameter Estimation for Satellite Image Restoration by a MCMCML Method.- Auxiliary Variables for Markov Random Fields with Higher Order Interactions.- Unsupervised Multispectral Image Segmentation Using Generalized Gaussian Noise Model.- Contours.- Adaptive Bayesian Contour Estimation: A Vector Space Representation Approach.- Adaptive Pixel-Based Data Fusion for Boundary Detection.- Search and Consistent Labeling.- Bayesian A* Tree Search with Expected O(N) Convergence Rates for Road Tracking.- A New Algorithm for Energy Minimization with Discontinuities.- Convergence of a Hill Climbing Genetic Algorithm for Graph Matching.- A New Distance Measure for Non-rigid Image Matching.- Continuous-Time Relaxation Labeling Processes.- Tracking and Video.- Realistic Animation Using Extended Adaptive Mesh for Model Based Coding.- Maximum Likelihood Inference of 3D Structure from Image Sequences.- Biomedical Applications.- Magnetic Resonance Imaging Based Correction and Reconstruction of Positron Emission Tomography Images.- Markov Random Field Modelling of fMRI Data Using a Mean Field EM-algorithm4.
Includes supplementary material: sn.pub/extras

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