Progress in Pattern Recognition
1st Edition
Published on 3. August 2007
Book
Hardback
XIII, 243 pages
978-1-84628-944-6 (ISBN)
Description
Overview andGoals Pattern recognition has evolved as a mature field of data analysis and its practice involves decision making using a wide variety of machine learning tools. Over the last three decades, substantial advances have been made in the areas of classification, prediction, optimisation and planning algorithms. Inparticular, the advances made in the areas of non-linear classification, statistical pattern recognition, multi-objective optimisation, string matching and uncertainty management are notable. These advances have been triggered by the availability of cheap computing power which allows large quantities of data to be processed in a very short period of time, and therefore developed algorithms can be tested easily on real problems. The current focus of pattern recognition research and development is to take laboratory solutions to commercial applications. The main goal of this book is to provide researchers with some of the latest novel techniques in the area of pattern recognition, and to show the potential of such techniques on real problems. The book will provide an excellent background to pattern recognition students and researchers into latest algorithms for pattern matching, and classification and their practical applications for imaging and non-imaging applications. Organization and Features The book is organised in two parts. The first nine chapters of the book describe novel advances in the areas of graph matching, information fusion, data clustering and classification, feature extraction and decision making under uncertainty.
Reviews / Votes
From the reviews:
"The book is divided into two parts. . Although in my opinion many articles could have presented more proper conclusions or deeper proofs and evidences, and some of them focused on the practicability of machine learning and pattern recognition from a theoretically point of view, the scientific relevance of the content of the book is good. The authors presented their work at the International Workshop on Advances in Pattern Recognition 2007. Accordingly, the target audience is also academic." (Eleazar Jimenez Serrano, IAPR Newsletter, Vol. 32 (4), October, 2010)More details
Series
Edition
1st Edition.
Language
English
Place of publication
London
United Kingdom
Target group
Professional and scholarly
Research
Product notice
Laminated cover
Illustrations
XIII, 243 p.
Dimensions
Height: 239 mm
Width: 159 mm
Thickness: 22 mm
Weight
550 gr
ISBN-13
978-1-84628-944-6 (9781846289446)
DOI
10.1007/978-1-84628-945-3
Schweitzer Classification
Other editions
Additional editions
Sameer Singh | Maneesha Singh
Progress in Pattern Recognition
Book
10/2010
Springer
€160.49
Shipment within 15-20 days
Persons
Professor Sameer Singh is Director of the Research School of Informatics, Loughborough University, UK, and serves as Editor-in-Chief of the Springer journal, Pattern Analysis and Applications
Content
Pattern Matching and Classification.- Estimation in Feedback Loops by Stochastic Learning.- Combining Exhaustive and Approximate Methods for Improved Sub-Graph Matching.- Information Fusion Techniques for Reliably Training Intrusion Detection Systems.- Use of Artificial Neural Networks and Effects of Amino Acid Encodings in the Membrane Protein Prediction Problem.- Computationally Efficient Graph Matching via Energy Vector Extraction.- A Validity Index Based on Cluster Symmetry.- of New Expert and Old Expert Retirement in Ensemble Learning under Drifting Concept.- Comparison of Three Feature Extraction Techniques to Distinguish Between Different Infrasound Signals.- Developing Trading Strategies based on Risk-analysis of Stocks.- Biometrics.- Facial Image Processing with Convolutional Neural Networks.- Time-dependent Interactive Graphical Models for Human Activity Analysis.- A New Lexicon-based Method for Automated Detection of Terrorist Web Documents.- A Neural Network Approach for Multifont and Size-Independent Recognition of Ethiopic Characters.- Automated Classification of Affective States using Facial Thermal Features.- On-line One Stroke Character Recognition Using Directional Features.- Comparison of SVMs in Number Plate Recognition.- Three Different Models for Named Entity Recognition in Bengali.- Comparison of Local and Global Thresholding for Binarization of Cheque Images.- Reading out 2D Barcode PDF417.- Off-Line Hand-Written Farsi/Arabic Word Segmentation into Subword under Overlapped or Connected Conditions.- Iris Biometrics Algorithm for Low Cost Devices.- Optimization on PCA Based Face Recognition Models.- Discriminating Unknown Faces using Eigen-face Approach and a Novelty Filter.- Using Timing to Detect Horror Shots in Horror Movies.- Indoor/Outdoor Scene Classification using Audio and Video Features.