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Computational Intelligence in Multi-Feature Visual Pattern Recognition: Hand Posture and Face Recognition using Biologically Inspired Approaches: 556 (Studies in Computational Intelligence) - Softcover

 
9789811011719: Computational Intelligence in Multi-Feature Visual Pattern Recognition: Hand Posture and Face Recognition using Biologically Inspired Approaches: 556 (Studies in Computational Intelligence)

Inhaltsangabe

This book presents a collection of computational intelligence algorithms that addresses issues in visual pattern recognition such as high computational complexity, abundance of pattern features, sensitivity to size and shape variations and poor performance against complex backgrounds. The book has 3 parts. Part 1 describes various research issues in the field with a survey of the related literature. Part 2 presents computational intelligence based algorithms for feature selection and classification. The algorithms are discriminative and fast. The main application area considered is hand posture recognition. The book also discusses utility of these algorithms in other visual as well as non-visual pattern recognition tasks including face recognition, general object recognition and cancer / tumor classification. Part 3 presents biologically inspired algorithms for feature extraction. The visual cortex model based features discussed have invariance with respect to appearance and size of the hand, and provide good inter class discrimination. A Bayesian model of visual attention is described which is effective in handling complex background problem in hand posture recognition.

The book provides qualitative and quantitative performance comparisons for the algorithms outlined, with other standard methods in machine learning and computer vision. The book is self-contained with several figures, charts, tables and equations helping the reader to understand the material presented without instruction.

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This book presents a collection of computational intelligence algorithms that addresses issues in visual pattern recognition such as high computational complexity, abundance of pattern features, sensitivity to size and shape variations and poor performance against complex backgrounds. The book has 3 parts. Part 1 describes various research issues in the field with a survey of the related literature. Part 2 presents computational intelligence based algorithms for feature selection and classification. The algorithms are discriminative and fast. The main application area considered is hand posture recognition. The book also discusses utility of these algorithms in other visual as well as non-visual pattern recognition tasks including face recognition, general object recognition and cancer / tumor classification. Part 3 presents biologically inspired algorithms for feature extraction. The visual cortex model based features discussed have invariance with respect to appearance and size of the hand, and provide good inter class discrimination. A Bayesian model of visual attention is described which is effective in handling complex background problem in hand posture recognition.

The book provides qualitative and quantitative performance comparisons for the algorithms outlined, with other standard methods in machine learning and computer vision. The book is self-contained with several figures, charts, tables and equations helping the reader to understand the material presented without instruction.

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  • VerlagSpringer
  • Erscheinungsdatum2016
  • ISBN 10 9811011710
  • ISBN 13 9789811011719
  • EinbandTapa blanda
  • SpracheEnglisch
  • Anzahl der Seiten156
  • Kontakt zum HerstellerNicht verfügbar

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9789812870551: Computational Intelligence in Multi-Feature Visual Pattern Recognition: Hand Posture and Face Recognition using Biologically Inspired Approaches: 556 (Studies in Computational Intelligence)

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ISBN 10:  9812870555 ISBN 13:  9789812870551
Verlag: Springer, 2014
Hardcover

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Pramod Kumar Pisharady
ISBN 10: 9811011710 ISBN 13: 9789811011719
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents a collection of computational intelligence algorithms that addresses issues in visual pattern recognition such as high computational complexity, abundance of pattern features, sensitivity to size and shape variations and poor performance against complex backgrounds. The book has 3 parts. Part 1 describes various research issues in the field with a survey of the related literature. Part 2 presents computational intelligence based algorithms for feature selection and classification. The algorithms are discriminative and fast. The main application area considered is hand posture recognition. The book also discusses utility of these algorithms in other visual as well as non-visual pattern recognition tasks including face recognition, general object recognition and cancer / tumor classification. Part 3 presents biologically inspired algorithms for feature extraction. The visual cortex model based features discussed have invariance with respect to appearance and size of the hand, and provide good inter class discrimination. A Bayesian model of visual attention is described which is effective in handling complex background problem in hand posture recognition.The book provides qualitative and quantitative performance comparisons for the algorithms outlined, with other standard methods in machine learning and computer vision. The book is self-contained with several figures, charts, tables and equations helping the reader to understand the material presented without instruction. Artikel-Nr. 9789811011719

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Pisharady, Pramod Kumar; Vadakkepat, Prahlad; Poh, Loh Ai
Verlag: Springer, 2016
ISBN 10: 9811011710 ISBN 13: 9789811011719
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