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S. Theodoridis & K. Koutroumbas - Pattern Recognition (Hardcover 3rd Ed) | NEW
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Located in: Denver, Colorado, United States
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eBay item number:136785604585
Item specifics
- Condition
- Brand New: A new, unread, unused book in perfect condition with no missing or damaged pages. See all condition definitionsopens in a new window or tab
- ISBN
- 9780123695314
About this product
Product Identifiers
Publisher
Elsevier Science & Technology
ISBN-10
0123695317
ISBN-13
9780123695314
eBay Product ID (ePID)
50359811
Product Key Features
Number of Pages
856 Pages
Publication Name
Pattern Recognition
Language
English
Subject
Data Modeling & Design, Intelligence (Ai) & Semantics, Databases / Data Mining, Computer Vision & Pattern Recognition
Publication Year
2006
Features
Revised
Type
Textbook
Subject Area
Computers
Format
Hardcover
Dimensions
Item Height
0.7 in
Item Length
9 in
Item Width
6 in
Additional Product Features
Edition Number
3
Intended Audience
College Audience
Reviews
"The book is written in a very readable, no-nonsense style. I found that there was just the right amount of text to describe a concept, without extraneous verbiage. The same is true for the mathematics, enough for description, not too much to overwhelm." Larry O'Gorman, IAPR Newsletter, April 2006, "The book is written in a very readable, no-nonsense style. I found that there was just the right amount of text to describe a concept ... " Larry O'Gorman, IAPR Newsletter, April 2006
Dewey Edition
21
Illustrated
Yes
Dewey Decimal
006.4
Table Of Content
Introduction; Classifiers Based on Bayes Decision Theory; Linear Classifiers; Nonlinear Classifiers; Feature Selection; Feature Generation I; Feature Generation II; Template Matching; Context-Dependant Classification; System Evaluation; Clustering: Basic Concepts Clustering Algorithms I (Sequential); Clustering Algorithms II (Hierarchical); Clustering Algorithms III (Functional Optimization); Clustering Algorithms IV (Graph Theory); Cluster Validity
Edition Description
Revised edition
Synopsis
Pattern recognition is a fast growing area with applications in a widely diverse number of fields such as communications engineering, bioinformatics, data mining, content-based database retrieval, to name but a few. This new edition addresses and keeps pace with the most recent advancements in these and related areas. This new edition: a) covers Data Mining, which was not treated in the previous edition, and is integrated with existing material in the book, b) includes new results on Learning Theory and Support Vector Machines, that are at the forefront of today's research, with a lot of interest both in academia and in applications-oriented communities, c) for the first time treats audio along with image applications since in today's world the most advanced applications are treated in a unified way and d) the subject of classifier combinations is treated, since this is a hot topic currently of interest in the pattern recognition community., Pattern recognition is a fast growing area with applications in a widely diverse number of fields such as communications engineering, bioinformatics, data mining, content-based database retrieval, to name but a few. This new edition addresses and keeps pace with the most recent advancements in these and related areas. This new edition: a) covers Data Mining, which was not treated in the previous edition, and is integrated with existing material in the book, b) includes new results on Learning Theory and Support Vector Machines, that are at the forefront of today's research, with a lot of interest both in academia and in applications-oriented communities, c) for the first time treats audio along with image applications since in today's world the most advanced applications are treated in a unified way and d) the subject of classifier combinations is treated, since this is a hot topic currently of interest in the pattern recognition community. The latest results on support vector machines including v-SVM's and their geometric interpretation Classifier combinations including the Boosting approach State-of-the-art material for clustering algorithms tailored for large data sets and/or high dimensional data, as required by applications such as web-mining and bioinformatics Coverage of diverse applications such as image analysis, optical character recognition, channel equalization, speech recognition and audio classification
LC Classification Number
TK7882.P3
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