Maneesha Singh - Böcker

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.

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.

This LNCS volume contains the papers presented at the 3rd International C- ferenceonAdvances in PatternRecognition(ICAPR2005)organizedin August, 2005 in the beautiful city of Bath, UK. The conference was ?rst organized in November 1998 in Plymouth, UK and subsequently in March 2001 in Rio de Janeiro, Brazil. The conference encouraged papers that made signi?cant th- reticalandapplication-basedcontributions inpatternrecognition. The emphasis was on an open exchange of ideas and shared learning. The papers submitted to ICAPR 2005 were thoroughly reviewed by up to three referees per paper and less than 40% of the submitted papers were accepted. The papers have been ?nally published as two volumes of LNCS and these are organized under the themes of Pattern Recognition and Data Mining (which included papers from the trackson PatternRecognition Methods, Knowledgeand Learning,and Data Mining), and Pattern Recognition and Image Analysis (which included papers from the Applications track). From the conference technical programme point of view, the ?rst volume contains papers on pattern recognition, data mining, signal processing and OCR/document analysis.The second volume contains - pers from the Workshop on Pattern Recognition for Crime Prevention, Security and Surveillance, Biometrics, Image Processing and Medical Imaging. ICAPR 2005was run in parallel with the InternationalWorkshop on Pattern Recognition for Crime Prevention, Security and Surveillance that was organized onthe22ndofAugust,2005. Thisworkshopbroughttogethera number ofexc- lent papers that focussed on how pattern recognition techniques can be used to developsystemsthathelpwithcrimepreventionanddetection. Onthesameday, a number of tutorials were also organized.