Pattern recognition: introduction, features, classifiers and principles
Beyerer, Jurgen
Pattern recognition: introduction, features, classifiers and principles - 2nd ed. - Oldenbourg: De Gruyter, 2024. - xxv, 327p.: col. ill.; pbk.: 24cm
Includes Bibliography, Glossary and 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 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 18 years lecture at the Karlsruhe Institute of Technology.
For students but also for practitioners.
https://www.degruyterbrill.com/document/doi/10.1515/9783111339207/html?lang=en&srsltid=AfmBOoqZNgI6xmjArhRUUG_FKAeVnb3Sd17ErWo6QZibnY9X_W812LZm
9783111339191
Pattern Recognition
Natural Sciences
Computational Intelligence
Applied Mathematics
Data Analysis
Machine Learning
006.4 BEY
Pattern recognition: introduction, features, classifiers and principles - 2nd ed. - Oldenbourg: De Gruyter, 2024. - xxv, 327p.: col. ill.; pbk.: 24cm
Includes Bibliography, Glossary and 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 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 18 years lecture at the Karlsruhe Institute of Technology.
For students but also for practitioners.
https://www.degruyterbrill.com/document/doi/10.1515/9783111339207/html?lang=en&srsltid=AfmBOoqZNgI6xmjArhRUUG_FKAeVnb3Sd17ErWo6QZibnY9X_W812LZm
9783111339191
Pattern Recognition
Natural Sciences
Computational Intelligence
Applied Mathematics
Data Analysis
Machine Learning
006.4 BEY
