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Applied Pattern Recognition

Editat de Horst Bunke, Abraham Kandel, Mark Last
en Limba Engleză Hardback – 11 apr 2008
A sharp increase in the computing power of modern computers, accompanied by a decrease in the data storage costs, has triggered the development of extremely powerful algorithms that can analyze complex patterns in large amounts of data within a very short period of time. Consequently, it has become possible to apply pattern recognition techniques to new tasks characterized by tight real-time requirements (e.g., person identification) and/or high complexity of raw data (e.g., clustering trajectories of mobile objects). The main goal of this book is to cover some of the latest application domains of pattern recognition while presenting novel techniques that have been developed or customized in those domains.
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Specificații

ISBN-13: 9783540768302
ISBN-10: 3540768300
Pagini: 260
Ilustrații: XII, 246 p. 110 illus., 51 illus. in color.
Dimensiuni: 160 x 241 x 21 mm
Greutate: 0.61 kg
Ediția:2008
Editura: Springer
Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Research

Cuprins

Face Recognition Applications.- Skin-based Face Detection-Extraction and Recognition of Facial Expressions.- Facial Image Processing.- Face Recognition and Pose Estimation with Parametric Linear Subspaces.- Spatio-Temporal Patterns.- 4D Segmentation of Cardiac Data Using Active Surfaces with Spatiotemporal Shape Priors.- Measuring Similarity Between Trajectories of Mobile Objects.- Graph-Based Methods.- Matching of Hypergraphs — Algorithms, Applications, and Experiments.- Feature-Driven Emergence of Model Graphs for Object Recognition and Categorization.- Special Applications.- A Wavelet-based Statistical Method for Chinese Writer Identification.- Texture Analysis by Accurate Identification of a Generic Markov–Gibbs Model.

Textul de pe ultima copertă

A sharp increase in the computing power of modern computers, accompanied by a decrease in the data storage costs, has triggered the development of extremely powerful algorithms that can analyze complex patterns in large amounts of data within a very short period of time. Consequently, it has become possible to apply pattern recognition techniques to new tasks characterized by tight real-time requirements (e.g., person identification) and/or high complexity of raw data (e.g., clustering trajectories of mobile objects). The main goal of this book is to cover some of the latest application domains of pattern recognition while presenting novel techniques that have been developed or customized in those domains.

Caracteristici

Recent results in applied pattern recognition Includes supplementary material: sn.pub/extras