Advances in Self-Organizing Maps and Learning Vector Quantization - Advances in Intelligent Systems and Computing
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Published By Springer International Publishing

9783319076942, 9783319076959

Latest Documents Most Cited Documents Contributed Authors Related Sources Related Keywords

Beyond Standard Metrics – On the Selection and Combination of Distance Metrics for an Improved Classification of Hyperspectral Data

Advances in Self-Organizing Maps and Learning Vector Quantization - Advances in Intelligent Systems and Computing ◽

10.1007/978-3-319-07695-9_16 ◽

2014 ◽

pp. 167-177 ◽

Cited By ~ 4

Author(s):

Uwe Knauer ◽

Andreas Backhaus ◽

Udo Seiffert

Keyword(s):

Hyperspectral Data ◽

Distance Metrics

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Rejection Strategies for Learning Vector Quantization – A Comparison of Probabilistic and Deterministic Approaches

Advances in Self-Organizing Maps and Learning Vector Quantization - Advances in Intelligent Systems and Computing ◽

10.1007/978-3-319-07695-9_10 ◽

2014 ◽

pp. 109-118 ◽

Cited By ~ 5

Author(s):

Lydia Fischer ◽

David Nebel ◽

Thomas Villmann ◽

Barbara Hammer ◽

Heiko Wersing

Keyword(s):

Vector Quantization ◽

Learning Vector Quantization

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Probability Ridges and Distortion Flows: Visualizing Multivariate Time Series Using a Variational Bayesian Manifold Learning Method

Advances in Self-Organizing Maps and Learning Vector Quantization - Advances in Intelligent Systems and Computing ◽

10.1007/978-3-319-07695-9_5 ◽

2014 ◽

pp. 55-64 ◽

Cited By ~ 1

Author(s):

Alessandra Tosi ◽

Iván Olier ◽

Alfredo Vellido

Keyword(s):

Time Series ◽

Manifold Learning ◽

Multivariate Time Series ◽

Learning Method ◽

Variational Bayesian

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How Many Dissimilarity/Kernel Self Organizing Map Variants Do We Need?

Advances in Self-Organizing Maps and Learning Vector Quantization - Advances in Intelligent Systems and Computing ◽

10.1007/978-3-319-07695-9_1 ◽

2014 ◽

pp. 3-23 ◽

Cited By ~ 5

Author(s):

Fabrice Rossi

Keyword(s):

Self Organizing Map ◽

Self Organizing

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Self-Organizing Map for the Prize-Collecting Traveling Salesman Problem

Advances in Self-Organizing Maps and Learning Vector Quantization - Advances in Intelligent Systems and Computing ◽

10.1007/978-3-319-07695-9_27 ◽

2014 ◽

pp. 281-291 ◽

Cited By ~ 3

Author(s):

Jan Faigl ◽

Geoffrey A. Hollinger

Keyword(s):

Traveling Salesman Problem ◽

Traveling Salesman ◽

Self Organizing Map ◽

Prize Collecting ◽

Self Organizing

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Some Room for GLVQ: Semantic Labeling of Occupancy Grid Maps

Advances in Self-Organizing Maps and Learning Vector Quantization - Advances in Intelligent Systems and Computing ◽

10.1007/978-3-319-07695-9_13 ◽

2014 ◽

pp. 133-143 ◽

Cited By ~ 1

Author(s):

Sven Hellbach ◽

Marian Himstedt ◽

Frank Bahrmann ◽

Martin Riedel ◽

Thomas Villmann ◽

...

Keyword(s):

Occupancy Grid ◽

Semantic Labeling ◽

Occupancy Grid Maps

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Attention Based Classification Learning in GLVQ and Asymmetric Misclassification Assessment

Advances in Self-Organizing Maps and Learning Vector Quantization - Advances in Intelligent Systems and Computing ◽

10.1007/978-3-319-07695-9_7 ◽

2014 ◽

pp. 77-87 ◽

Cited By ~ 1

Author(s):

Marika Kaden ◽

W. Hermann ◽

Thomas Villmann

Keyword(s):

Classification Learning

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Generative versus Discriminative Prototype Based Classification

Advances in Self-Organizing Maps and Learning Vector Quantization - Advances in Intelligent Systems and Computing ◽

10.1007/978-3-319-07695-9_12 ◽

2014 ◽

pp. 123-132 ◽

Cited By ~ 6

Author(s):

Barbara Hammer ◽

David Nebel ◽

Martin Riedel ◽

Thomas Villmann

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A Biologically Plausible SOM Representation of the Orthographic Form of 50,000 French Words

Advances in Self-Organizing Maps and Learning Vector Quantization - Advances in Intelligent Systems and Computing ◽

10.1007/978-3-319-07695-9_29 ◽

2014 ◽

pp. 303-312 ◽

Cited By ~ 2

Author(s):

Claude Touzet ◽

Christopher Kermorvant ◽

Hervé Glotin

Keyword(s):

French Words

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A Concurrent SOM-Based Chan-Vese Model for Image Segmentation

Advances in Self-Organizing Maps and Learning Vector Quantization - Advances in Intelligent Systems and Computing ◽

10.1007/978-3-319-07695-9_19 ◽

2014 ◽

pp. 199-208 ◽

Cited By ~ 8

Author(s):

Mohammed M. Abdelsamea ◽

Giorgio Gnecco ◽

Mohamed Medhat Gaber

Keyword(s):

Image Segmentation

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Advances in Self-Organizing Maps and Learning Vector Quantization - Advances in Intelligent Systems and ComputingLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer International Publishing

Beyond Standard Metrics – On the Selection and Combination of Distance Metrics for an Improved Classification of Hyperspectral Data

Rejection Strategies for Learning Vector Quantization – A Comparison of Probabilistic and Deterministic Approaches

Probability Ridges and Distortion Flows: Visualizing Multivariate Time Series Using a Variational Bayesian Manifold Learning Method

How Many Dissimilarity/Kernel Self Organizing Map Variants Do We Need?

Self-Organizing Map for the Prize-Collecting Traveling Salesman Problem

Some Room for GLVQ: Semantic Labeling of Occupancy Grid Maps

Attention Based Classification Learning in GLVQ and Asymmetric Misclassification Assessment

Generative versus Discriminative Prototype Based Classification

A Biologically Plausible SOM Representation of the Orthographic Form of 50,000 French Words

A Concurrent SOM-Based Chan-Vese Model for Image Segmentation

Advances in Self-Organizing Maps and Learning Vector Quantization - Advances in Intelligent Systems and Computing
Latest Publications