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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| Hauptverfasser: | , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Berlin ; Boston :
Walter de Gruyter GmbH,
[2018]
|
| Schriftenreihe: | De Gruyter graduate.
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | 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. |
| Beschreibung: | 1 online resource |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 9783110537963 3110537966 9783110537949 311053794X |
Internformat
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| 505 | 0 | 0 | |t Frontmatter -- |t Preface -- |t Contents -- |t List of Tables -- |t List of Figures -- |t Notation -- |t Introduction -- |t 1. Fundamentals and definitions -- |t 2. Features -- |t 3. Bayesian decision theory -- |t 4. Parameter estimation -- |t 5. Parameter free methods -- |t 6. General considerations -- |t 7. Special classifiers -- |t 8. Classification with nominal features -- |t 9. Classifier-independent concepts -- |t A. Solutions to the exercises -- |t B.A primer on Lie theory -- |t C. Random processes -- |t Bibliography -- |t Glossary -- |t Index. |
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| author | Beyerer, Jürgen Richter, Matthias, 1948- Nagel, Matthias (Computer scientist) |
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| 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. |
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| discipline | Informatik |
| format | Electronic eBook |
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| series | De Gruyter graduate. |
| series2 | De Gruyter graduate |
| spelling | Beyerer, Jürgen, author. http://id.loc.gov/authorities/names/n2018001459 Pattern recognition : introduction, features, classifiers and principles / Jürgen Beyerer, Matthias Richter, Matthias Nagel. Berlin ; Boston : Walter de Gruyter GmbH, [2018] ©2018 1 online resource text txt rdacontent computer c rdamedia online resource cr rdacarrier De Gruyter graduate Includes bibliographical references and index. Vendor-supplied metadata. 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. 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. Pattern recognition systems. http://id.loc.gov/authorities/subjects/sh85098791 Pattern Recognition, Automated https://id.nlm.nih.gov/mesh/D010363 Reconnaissance des formes (Informatique) COMPUTERS General. bisacsh Pattern recognition systems fast Mustererkennung gnd http://d-nb.info/gnd/4040936-3 Automatische Klassifikation gnd http://d-nb.info/gnd/4120957-6 Merkmalsextraktion gnd http://d-nb.info/gnd/4314440-8 Electronic book. Richter, Matthias, 1948- author. https://id.oclc.org/worldcat/entity/E39PCjJBBdgvt8HMkCwXJ3cfD3 http://id.loc.gov/authorities/names/n93033435 Nagel, Matthias (Computer scientist), author. https://id.oclc.org/worldcat/entity/E39PCjxvmktcBjcPVY9FKgkcmq http://id.loc.gov/authorities/names/n2018001460 has work: Pattern recognition (Text) https://id.oclc.org/worldcat/entity/E39PCFR4JDqCbjQMX7Vh64TvHC https://id.oclc.org/worldcat/ontology/hasWork Print version: Beyerer, Jürgen. Pattern recognition. Berlin ; Boston : Walter de Gruyter GmbH, [2018] 9783110537932 (DLC) 2017054350 (OCoLC)1019833485 De Gruyter graduate. http://id.loc.gov/authorities/names/no2011117424 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1658997 Volltext |
| spellingShingle | Beyerer, Jürgen Richter, Matthias, 1948- Nagel, Matthias (Computer scientist) Pattern recognition : introduction, features, classifiers and principles / De Gruyter graduate. 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. Pattern recognition systems. http://id.loc.gov/authorities/subjects/sh85098791 Pattern Recognition, Automated https://id.nlm.nih.gov/mesh/D010363 Reconnaissance des formes (Informatique) COMPUTERS General. bisacsh Pattern recognition systems fast Mustererkennung gnd http://d-nb.info/gnd/4040936-3 Automatische Klassifikation gnd http://d-nb.info/gnd/4120957-6 Merkmalsextraktion gnd http://d-nb.info/gnd/4314440-8 |
| subject_GND | http://id.loc.gov/authorities/subjects/sh85098791 https://id.nlm.nih.gov/mesh/D010363 http://d-nb.info/gnd/4040936-3 http://d-nb.info/gnd/4120957-6 http://d-nb.info/gnd/4314440-8 |
| title | 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_auth | Pattern recognition : introduction, features, classifiers and principles / |
| title_exact_search | Pattern recognition : 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_short | Pattern recognition : |
| title_sort | pattern recognition introduction features classifiers and principles |
| title_sub | introduction, features, classifiers and principles / |
| topic | Pattern recognition systems. http://id.loc.gov/authorities/subjects/sh85098791 Pattern Recognition, Automated https://id.nlm.nih.gov/mesh/D010363 Reconnaissance des formes (Informatique) COMPUTERS General. bisacsh Pattern recognition systems fast Mustererkennung gnd http://d-nb.info/gnd/4040936-3 Automatische Klassifikation gnd http://d-nb.info/gnd/4120957-6 Merkmalsextraktion gnd http://d-nb.info/gnd/4314440-8 |
| topic_facet | Pattern recognition systems. Pattern Recognition, Automated Reconnaissance des formes (Informatique) COMPUTERS General. Pattern recognition systems Mustererkennung Automatische Klassifikation Merkmalsextraktion Electronic book. |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1658997 |
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