Artificial Neural Networks in Pattern Recognition : 5th INNS IAPR TC 3 GIRPR Workshop, ANNPR 2012, Trento, Italy, September 17-19, 2012, Proceedings / edited by Nadia Mana, Friedhelm Schwenker, Edmondo Trentin.

Format:

Book

Contributor:

Mana, Nadia, editor.

Schwenker, Friedhelm, editor.

Trentin, Edmondo, editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Lecture notes in computer science. Lecture notes in artificial intelligence ; 7477.

Lecture Notes in Artificial Intelligence ; 7477

Language:

English

Subjects (All):

Artificial intelligence.

Pattern perception.

Data mining.

Optical data processing.

User interfaces (Computer systems).

Artificial Intelligence.

Pattern Recognition.

Data Mining and Knowledge Discovery.

Image Processing and Computer Vision.

User Interfaces and Human Computer Interaction.

Computer Imaging, Vision, Pattern Recognition and Graphics.

Local Subjects:

Artificial Intelligence.

Pattern Recognition.

Data Mining and Knowledge Discovery.

Image Processing and Computer Vision.

User Interfaces and Human Computer Interaction.

Computer Imaging, Vision, Pattern Recognition and Graphics.

Physical Description:

1 online resource (X, 245 pages) : 80 illustrations.

Edition:

First edition 2012.

Contained In:

Springer eBooks

Place of Publication:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2012.

System Details:

text file PDF

Summary:

This book constitutes the refereed proceedings of the 5th INNS IAPR TC3 GIRPR International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2012, held in Trento, Italy, in September 2012. The 21 revised full papers presented were carefully reviewed and selected for inclusion in this volume. They cover a large range of topics in the field of neural network- and machine learning-based pattern recognition presenting and discussing the latest research, results, and ideas in these areas.

Contents:

Learning Algorithms

How to Quantitatively Compare Data Dissimilarities for Unsupervised Machine Learning?- Kernel Robust Soft Learning Vector Quantization

Incremental Learning by Message Passing in Hierarchical Temporal

Representative Prototype Sets for Data Characterization and Classification

Feature Selection by Block Addition and Block Deletion

Gradient Algorithms for Exploration/Exploitation Trade-Offs: Global and Local Variants

Towards a Novel Probabilistic Graphical Model of Sequential Data: Fundamental Notions and a Solution to the Problem of Parameter Learning

Towards a Novel Probabilistic Graphical Model of Sequential Data: A Solution to the Problem of Structure Learning and an Empirical Evaluation

Statistical Recognition of a Set of Patterns Using Novel Probability Neural Network

On Graph-Associated Matrices and Their Eigenvalues for Optical Character Recognition

Classification of Segmented Objects through a Multi-net Approach

On Instance Selection in Audio Based Emotion Recognition

Grayscale Images and RGB Video: Compression by Morphological Neural Network

NeuCube EvoSpike Architecture for Spatio-temporal Modelling and Pattern Recognition of Brain Signals.

Other Format:

Printed edition:

ISBN:

978-3-642-33212-8

9783642332128

Access Restriction:

Restricted for use by site license.