Pattern recognition introduction, features, classifiers and principles

The book offers a thorough introduction to Pattern Recognition aimed at master and advanced bachelor students of engineering and the natural sciences. Besides classification - the heart of Pattern Recognition - special emphasis is put on features, their typology, their properties and their systemati...

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Bibliographic Details
Main Author: Beyerer, Jürgen
Other Authors: Richter, Matthias, Nagel, Matthias
Format: eBook
Language:English
Published: Berlin ; Boston De Gruyter 2017, ©2018
Series:De Gruyter Textbook
Subjects:
Online Access:
Collection: DeGruyter MPG Collection - Collection details see MPG.ReNa
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245 0 0 |a Pattern recognition  |h Elektronische Ressource  |b introduction, features, classifiers and principles  |c Jürgen Beyerer, Matthias Richter, Matthias Nagel 
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300 |a XXVIII, 283 Seiten 
653 |a Informatik / Künstliche Intelligenz 
653 |a Computer Sciences / Artificial Intelligence 
653 |a Engineering / Electrical Engineering / Signal Processing 
653 |a Informatik / Datenbanken und Data Mining 
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700 1 |a Nagel, Matthias 
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520 3 |a The book offers a thorough introduction to Pattern Recognition aimed at master and advanced bachelor students of engineering and the natural sciences. Besides classification - the heart of Pattern Recognition - special emphasis is put on features, their typology, their properties and their systematic construction. Additionally, general principles that govern Pattern Recognition are illustrated and explained in a comprehensible way. Rather than presenting a complete overview over the rapidly evolving field, the book is to clarifies the concepts so that the reader can easily understand the underlying ideas and the rationale behind the methods. For this purpose, the mathematical treatment of Pattern Recognition is pushed so far that the mechanisms of action become clear and visible, but not farther. Therefore, not all derivations are driven into the last mathematical detail, as a mathematician would expect it. Ideas of proofs are presented instead of complete proofs. From the authors’ point of view, this concept allows to teach the essential ideas of Pattern Recognition with sufficient depth within a relatively lean book.