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Evolutionary Synthesis of Pattern Recognition Systems
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ISBN: 9781441919434

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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 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 book achieves four aims: *Shows the efficacy of genetic programming and coevolutionary genetic programming in synthesizing effective composite operators and composite features from domain-independent primitive image processing operations and primitive features (both elementary and complex) for object detection and recognition. *Integrates smart crossover, smart mutation and a new fitness function based on minimum description length (MDL) principle in a design to improve genetic programming's efficiency*Proposes a new MDL-based fitness function to improve the genetic algorithm's performance on feature selection for object detection and recognition*Synthesizes recognition systems by using adaptive coevolutionary linear genetic programming (LGP) in conjunction with general computer vision and image processing operatorsThe 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 Textbooks New, Books~~Computers~~Image Processing, Evolutionary-Synthesis-of-Pattern-Recognition-Systems~~Bir-Bhanu, , , , , , , , , , Springer New York

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ISBN: 9781441919434

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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 book achieves four aims: *Shows the efficacy of genetic programming and coevolutionary genetic programming in synthesizing effective composite operators and composite features from domain-independent primitive image processing operations and primitive features (both elementary and complex) for object detection and recognition. *Integrates smart crossover, smart mutation and a new fitness function based on minimum description length (MDL) principle in a design to improve genetic programming''s efficiency*Proposes a new MDL-based fitness function to improve the genetic algorithm''s performance on feature selection for object detection and recognition.*Synthesizes recognition systems by using adaptive coevolutionary linear genetic programming (LGP) in conjunction with general computer vision and image processing operatorsThe 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. Bir Bhanu, Books, Computers, Evolutionary Synthesis of Pattern Recognition Systems Books>Computers, Springer New York

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Evolutionary Synthesis Of Pattern Recognition Systems
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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 Books, Computing~~Computer Science~~Artificial Intelligence, Evolutionary Synthesis Of Pattern Recognition Systems~~Book~~9781441919434~~Bir Bhanu, Yingqiang Lin, Krzysztof Krawiec, , , , , , , , , ,, [PU: Springer]

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Evolutionary Synthesis of Pattern Recognition Systems ab 165.49 EURO Monographs in Computer Science. Softcover reprint of hardcover 1st ed. 2005. Evolutionary Synthesis of Pattern Recognition Systems ab 165.49 EURO Monographs in Computer Science. Softcover reprint of hardcover 1st ed. 2005. Bücher > English, International > Gebundene Ausgaben, [PU: Springer]

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Evolutionary Synthesis of Pattern Recognition Systems:Softcover reprint of hardcover 1st ed. 2005. Bir Bhanu, Krzysztof Krawiec, Lin Yingqiang Evolutionary Synthesis of Pattern Recognition Systems:Softcover reprint of hardcover 1st ed. 2005. Bir Bhanu, Krzysztof Krawiec, Lin Yingqiang Bücher > English, International > Gebundene Ausgaben, Springer

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Evolutionary Synthesis of Pattern Recognition Systems

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

Detailangaben zum Buch - Evolutionary Synthesis of Pattern Recognition Systems


EAN (ISBN-13): 9781441919434
ISBN (ISBN-10): 1441919430
Gebundene Ausgabe
Taschenbuch
Erscheinungsjahr: 2010
Herausgeber: Springer-Verlag GmbH
320 Seiten
Gewicht: 0,485 kg
Sprache: eng/Englisch

Buch in der Datenbank seit 28.08.2011 14:40:02
Buch zuletzt gefunden am 01.11.2017 20:29:46
ISBN/EAN: 1441919430

ISBN - alternative Schreibweisen:
1-4419-1943-0, 978-1-4419-1943-4


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