Pattern Recognition : : Introduction, Features, Classifiers and Principles / / Jürgen Beyerer, Matthias Richter, Matthias Nagel.
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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Place / Publishing House: | München ;, Wien : : De Gruyter Oldenbourg, , [2017] ©2018 |
Year of Publication: | 2017 |
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Beyerer, Jürgen, author. aut http://id.loc.gov/vocabulary/relators/aut Pattern Recognition : Introduction, Features, Classifiers and Principles / Jürgen Beyerer, Matthias Richter, Matthias Nagel. München ; Wien : De Gruyter Oldenbourg, [2017] ©2018 1 online resource (XXVIII, 283 p.) text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda De Gruyter Textbook Frontmatter -- Preface -- Contents -- List of Tables -- List of Figures -- Notation -- Introduction -- 1. Fundamentals and definitions -- 2. Features -- 3. Bayesian decision theory -- 4. Parameter estimation -- 5. Parameter free methods -- 6. General considerations -- 7. Special classifiers -- 8. Classification with nominal features -- 9. Classifier-independent concepts -- A. Solutions to the exercises -- B. A primer on Lie theory -- C. Random processes -- Bibliography -- Glossary -- Index restricted access http://purl.org/coar/access_right/c_16ec online access with authorization star 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. Mathematical methods explained thoroughly Extremely practical approach with many examples Based on over ten years lecture at Karlsruhe Institute of Technology For students but also for practitioners 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. Mathematical methods explained thoroughlyExtremely practical approach with many examplesBased on over ten years lecture at Karlsruhe Institute of TechnologyFor students but also for practitioners Mode of access: Internet via World Wide Web. In English. Description based on online resource; title from PDF title page (publisher's Web site, viewed 30. Aug 2021) Pattern recognition systems. Artificial Intelligence. Automation. Data Mining. Machine Learning. Beyerer, Jürgen, contributor. ctb https://id.loc.gov/vocabulary/relators/ctb Nagel, Matthias, author. aut http://id.loc.gov/vocabulary/relators/aut Nagel, Matthias, contributor. ctb https://id.loc.gov/vocabulary/relators/ctb Richter, Matthias, author. aut http://id.loc.gov/vocabulary/relators/aut Richter, Matthias, contributor. ctb https://id.loc.gov/vocabulary/relators/ctb Title is part of eBook package: De Gruyter DG OWV ebook Paket Lehrbücher Technik und Informatik 2017 9783110549218 ZDB-23-OTI Title is part of eBook package: De Gruyter DG Plus eBook-Package 2018 9783110719550 Title is part of eBook package: De Gruyter EBOOK PACKAGE COMPLETE 2017 9783110540550 ZDB-23-DGG Title is part of eBook package: De Gruyter EBOOK PACKAGE COMPLETE ENGLISH 2017 9783110625264 Title is part of eBook package: De Gruyter EBOOK PACKAGE Engineering, Computer Sciences 2017 9783110547757 ZDB-23-DEI EPUB 9783110537963 print 9783110537932 https://doi.org/10.1515/9783110537949 https://www.degruyter.com/isbn/9783110537949 Cover https://www.degruyter.com/cover/covers/9783110537949.jpg |
language |
English |
format |
eBook |
author |
Beyerer, Jürgen, Beyerer, Jürgen, Nagel, Matthias, Richter, Matthias, |
spellingShingle |
Beyerer, Jürgen, Beyerer, Jürgen, Nagel, Matthias, Richter, Matthias, Pattern Recognition : Introduction, Features, Classifiers and Principles / De Gruyter Textbook Frontmatter -- Preface -- Contents -- List of Tables -- List of Figures -- Notation -- Introduction -- 1. Fundamentals and definitions -- 2. Features -- 3. Bayesian decision theory -- 4. Parameter estimation -- 5. Parameter free methods -- 6. General considerations -- 7. Special classifiers -- 8. Classification with nominal features -- 9. Classifier-independent concepts -- A. Solutions to the exercises -- B. A primer on Lie theory -- C. Random processes -- Bibliography -- Glossary -- Index |
author_facet |
Beyerer, Jürgen, Beyerer, Jürgen, Nagel, Matthias, Richter, Matthias, Beyerer, Jürgen, Beyerer, Jürgen, Nagel, Matthias, Nagel, Matthias, Nagel, Matthias, Nagel, Matthias, Richter, Matthias, Richter, Matthias, Richter, Matthias, Richter, Matthias, |
author_variant |
j b jb j b jb m n mn m r mr |
author_role |
VerfasserIn VerfasserIn VerfasserIn VerfasserIn |
author2 |
Beyerer, Jürgen, Beyerer, Jürgen, Nagel, Matthias, Nagel, Matthias, Nagel, Matthias, Nagel, Matthias, Richter, Matthias, Richter, Matthias, Richter, Matthias, Richter, Matthias, |
author2_variant |
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MitwirkendeR MitwirkendeR VerfasserIn VerfasserIn MitwirkendeR MitwirkendeR VerfasserIn VerfasserIn MitwirkendeR MitwirkendeR |
author_sort |
Beyerer, Jürgen, |
title |
Pattern Recognition : Introduction, Features, Classifiers and Principles / |
title_sub |
Introduction, Features, Classifiers and Principles / |
title_full |
Pattern Recognition : Introduction, Features, Classifiers and Principles / Jürgen Beyerer, Matthias Richter, Matthias Nagel. |
title_fullStr |
Pattern Recognition : Introduction, Features, Classifiers and Principles / Jürgen Beyerer, Matthias Richter, Matthias Nagel. |
title_full_unstemmed |
Pattern Recognition : Introduction, Features, Classifiers and Principles / Jürgen Beyerer, Matthias Richter, Matthias Nagel. |
title_auth |
Pattern Recognition : Introduction, Features, Classifiers and Principles / |
title_alt |
Frontmatter -- Preface -- Contents -- List of Tables -- List of Figures -- Notation -- Introduction -- 1. Fundamentals and definitions -- 2. Features -- 3. Bayesian decision theory -- 4. Parameter estimation -- 5. Parameter free methods -- 6. General considerations -- 7. Special classifiers -- 8. Classification with nominal features -- 9. Classifier-independent concepts -- A. Solutions to the exercises -- B. A primer on Lie theory -- C. Random processes -- Bibliography -- Glossary -- Index |
title_new |
Pattern Recognition : |
title_sort |
pattern recognition : introduction, features, classifiers and principles / |
series |
De Gruyter Textbook |
series2 |
De Gruyter Textbook |
publisher |
De Gruyter Oldenbourg, |
publishDate |
2017 |
physical |
1 online resource (XXVIII, 283 p.) |
contents |
Frontmatter -- Preface -- Contents -- List of Tables -- List of Figures -- Notation -- Introduction -- 1. Fundamentals and definitions -- 2. Features -- 3. Bayesian decision theory -- 4. Parameter estimation -- 5. Parameter free methods -- 6. General considerations -- 7. Special classifiers -- 8. Classification with nominal features -- 9. Classifier-independent concepts -- A. Solutions to the exercises -- B. A primer on Lie theory -- C. Random processes -- Bibliography -- Glossary -- Index |
isbn |
9783110537949 9783110549218 9783110719550 9783110540550 9783110625264 9783110547757 9783110537963 9783110537932 |
callnumber-first |
T - Technology |
callnumber-subject |
TK - Electrical and Nuclear Engineering |
callnumber-label |
TK7882 |
callnumber-sort |
TK 47882 P3 B45 42018 |
url |
https://doi.org/10.1515/9783110537949 https://www.degruyter.com/isbn/9783110537949 https://www.degruyter.com/cover/covers/9783110537949.jpg |
illustrated |
Not Illustrated |
doi_str_mv |
10.1515/9783110537949 |
oclc_num |
1015878284 |
work_keys_str_mv |
AT beyererjurgen patternrecognitionintroductionfeaturesclassifiersandprinciples AT nagelmatthias patternrecognitionintroductionfeaturesclassifiersandprinciples AT richtermatthias patternrecognitionintroductionfeaturesclassifiersandprinciples |
status_str |
n |
ids_txt_mv |
(DE-B1597)479058 (OCoLC)1015878284 |
carrierType_str_mv |
cr |
hierarchy_parent_title |
Title is part of eBook package: De Gruyter DG OWV ebook Paket Lehrbücher Technik und Informatik 2017 Title is part of eBook package: De Gruyter DG Plus eBook-Package 2018 Title is part of eBook package: De Gruyter EBOOK PACKAGE COMPLETE 2017 Title is part of eBook package: De Gruyter EBOOK PACKAGE COMPLETE ENGLISH 2017 Title is part of eBook package: De Gruyter EBOOK PACKAGE Engineering, Computer Sciences 2017 |
is_hierarchy_title |
Pattern Recognition : Introduction, Features, Classifiers and Principles / |
container_title |
Title is part of eBook package: De Gruyter DG OWV ebook Paket Lehrbücher Technik und Informatik 2017 |
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