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Similarity-Based Clustering of Sequences Using Hidden Markov Models

Lecture notes in computer science, 2003, Vol.2734, p.86-95

2003

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Local Features Applied to Dermoscopy Images: Bag-of-Features versus Sparse Coding

Pattern Recognition and Image Analysis, 2017, Vol.10255, p.528-536

2017

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Exploiting the Bin-Class Histograms for Feature Selection on Discrete Data

Pattern Recognition and Image Analysis, 2015, Vol.9117, p.345-353

2015

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On the suitability of suffix arrays for lempel-ziv data compression

e-Business and Telecommunications, 2009, Vol.48, p.267-280

2009

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Pattern Recognition: Applications and Methods: 4th International Conference, ICPRAM 2015, Lisbon, Portugal, January 10-12, 2015, Revised Selected Papers

1st ed. 2015, 2015

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Iterative Imputation of Missing Data Using Auto-Encoder Dynamics

Neural Information Processing, 2020, Vol.12534, p.258-269

2020

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An Experimental Comparison of Min-cut/Max-flow Algorithms for Energy Minimization in Vision

Energy Minimization Methods in Computer Vision and Pattern Recognition, 2001, Vol.2134, p.359-374

2001

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Sharpening Hyperspectral Images Using Plug-and-Play Priors

Latent Variable Analysis and Signal Separation, 2017, Vol.10169, p.392-402

2017

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Sharpening Hyperspectral Images Using Spatial and Spectral Priors in a Plug-and-Play Algorithm

Energy Minimization Methods in Computer Vision and Pattern Recognition, 2018, Vol.10746, p.358-371

2018

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Trajectory Modeling Using Mixtures of Vector Fields

Pattern Recognition and Image Analysis, 2009, Vol.5524, p.40-47

2009

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Path Based Pairwise Data Clustering with Application to Texture Segmentation

Energy Minimization Methods in Computer Vision and Pattern Recognition, 2001, Vol.2134, p.235-250

2001

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A Generative Dyadic Aspect Model for Evidence Accumulation Clustering

Similarity-Based Pattern Recognition, 2011, Vol.7005, p.104-116

2011

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Curvature Vector Flow to Assure Convergent Deformable Models for Shape Modelling

Energy Minimization Methods in Computer Vision and Pattern Recognition, 2003, Vol.2683, p.357-372

2003

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Estimation of Rank Deficient Matrices from Partial Observations: Two-Step Iterative Algorithms

Energy Minimization Methods in Computer Vision and Pattern Recognition, 2003, Vol.2683, p.450-466

2003

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Generalized Multi-camera Scene Reconstruction Using Graph Cuts

Energy Minimization Methods in Computer Vision and Pattern Recognition, 2003, Vol.2683, p.501-516

2003

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Generalizing the Motzkin-Straus Theorem to Edge-Weighted Graphs, with Applications to Image Segmentation

Energy Minimization Methods in Computer Vision and Pattern Recognition, 2003, Vol.2683, p.485-500

2003

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A Variational Approach to Maximum a Posteriori Estimation for Image Denoising

Energy Minimization Methods in Computer Vision and Pattern Recognition, 2001, Vol.2134, p.19-34

2001

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Estimation of Distribution Algorithms: A New Evolutionary Computation Approach for Graph Matching Problems

Energy Minimization Methods in Computer Vision and Pattern Recognition, 2001, Vol.2134, p.454-469

2001

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Averaged Template Matching Equations

Energy Minimization Methods in Computer Vision and Pattern Recognition, 2001, Vol.2134, p.528-543

2001

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Definition of a Signal-to-Noise Ratio for Object Segmentation Using Polygonal MDL-Based Statistical Snakes

Energy Minimization Methods in Computer Vision and Pattern Recognition, 2003, Vol.2683, p.373-388

2003

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Efficiently Computing Weighted Tree Edit Distance Using Relaxation Labeling

Energy Minimization Methods in Computer Vision and Pattern Recognition, 2001, Vol.2134, p.438-453

2001

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Using Prior Shape and Points in Medical Image Segmentation

Energy Minimization Methods in Computer Vision and Pattern Recognition, 2003, Vol.2683, p.291-305

2003

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A MAP Estimation Algorithm Using IIR Recursive Filters

Energy Minimization Methods in Computer Vision and Pattern Recognition, 2003, Vol.2683, p.436-449

2003

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Grouping with Directed Relationships

Energy Minimization Methods in Computer Vision and Pattern Recognition, 2001, Vol.2134, p.283-297

2001

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Surface Recovery from 3D Point Data Using a Combined Parametric and Geometric Flow Approach

Energy Minimization Methods in Computer Vision and Pattern Recognition, 2003, Vol.2683, p.325-340

2003

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Similarity-Based Clustering of Sequences Using Hidden Markov Models

Local Features Applied to Dermoscopy Images: Bag-of-Features versus Sparse Coding

Exploiting the Bin-Class Histograms for Feature Selection on Discrete Data

On the suitability of suffix arrays for lempel-ziv data compression

Pattern Recognition: Applications and Methods: 4th International Conference, ICPRAM 2015, Lisbon, Portugal, January 10-12, 2015, Revised Selected Papers

Iterative Imputation of Missing Data Using Auto-Encoder Dynamics

An Experimental Comparison of Min-cut/Max-flow Algorithms for Energy Minimization in Vision

Sharpening Hyperspectral Images Using Plug-and-Play Priors

Sharpening Hyperspectral Images Using Spatial and Spectral Priors in a Plug-and-Play Algorithm

Trajectory Modeling Using Mixtures of Vector Fields

Path Based Pairwise Data Clustering with Application to Texture Segmentation

A Generative Dyadic Aspect Model for Evidence Accumulation Clustering

Curvature Vector Flow to Assure Convergent Deformable Models for Shape Modelling

Estimation of Rank Deficient Matrices from Partial Observations: Two-Step Iterative Algorithms

Generalized Multi-camera Scene Reconstruction Using Graph Cuts

Generalizing the Motzkin-Straus Theorem to Edge-Weighted Graphs, with Applications to Image Segmentation

A Variational Approach to Maximum a Posteriori Estimation for Image Denoising

Estimation of Distribution Algorithms: A New Evolutionary Computation Approach for Graph Matching Problems

Averaged Template Matching Equations

Definition of a Signal-to-Noise Ratio for Object Segmentation Using Polygonal MDL-Based Statistical Snakes

Efficiently Computing Weighted Tree Edit Distance Using Relaxation Labeling

Using Prior Shape and Points in Medical Image Segmentation

A MAP Estimation Algorithm Using IIR Recursive Filters

Grouping with Directed Relationships

Surface Recovery from 3D Point Data Using a Combined Parametric and Geometric Flow Approach

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