Evolutionary Synthesis of Pattern Recognition Systems

Bir Bhanu

ISBN 10: 0387212957 / ISBN 13: 9780387212951

Edité par Springer New York Feb 2005, 2005

A propos de cet article

Neuware - Evolutionary computation is becoming increasingly important for computer vision and pattern recognition and provides a systematic way of synthesis and analysis of object detection and recognition systems. Incorporating 'learning' into recognition systems will enable these systems to automatically generate new features on the fly and cleverly select a good subset of features according to the type of objects and images to which they are applied.This unique monograph investigates evolutionary computational techniques--such as genetic programming, linear genetic programming, coevolutionary genetic programming and genetic algorithms--to automate the synthesis and analysis of object detection and recognition systems.The purpose of incorporating learning into the system design is to avoid the time-consuming process of feature generation and selection and to reduce the cost of building object detection and recognition systems.Researchers, professionals, engineers, and students working in computer vision, pattern recognition, target recognition, machine learning, evolutionary learning, image processing, knowledge discovery and data mining, cybernetics, robotics, automation and psychology will find this well-developed and organized volume an invaluable resource.

N° de réf. du vendeur 9780387212951

Détails bibliographiques

• Titre: Evolutionary Synthesis of Pattern Recognition Systems
• Éditeur: Springer New York Feb 2005
• Date de parution: 2005
• Langue: anglais
• ISBN à 10 chiffres: 0387212957
• ISBN à 13 chiffres: 9780387212951
• Reliure: Buch
• État de l'article: Neu

A propos de ce titre

Synopsis

Evolutionary computation is becoming increasingly important for computer vision and pattern recognition. It provides a systematic way of synthesizing and analyzing object detection and pattern recognition systems. Incorporating "learning" into recognition systems will enable these systems to automatically generate new features on the fly (evolve) and cleverly select a good subset of features according to the type of objects and images to which they are applied. This book investigates evolutionary computational techniques---such as genetic programming, linear genetic programming, coevolutionary genetic programming and genetic algorithms---to automate the synthesis and analysis of object detection and recognition systems.

Présentation de l'éditeur

Integrates computer vision, pattern recognition, and AI. Presents original research that will benefit researchers and professionals in computer vision, pattern recognition, target recognition, machine learning, evolutionary learning, image processing, knowledge discovery and data mining, cybernetics, robotics, automation and psychology