Jianxin Wu

Essentials of Pattern Recognition (eBook, PDF)

An Accessible Approach

• Format: PDF

Produktbeschreibung

This textbook introduces fundamental concepts, major models, and popular applications of pattern recognition for a one-semester undergraduate course. To ensure student understanding, the text focuses on a relatively small number of core concepts with an abundance of illustrations and examples. Concepts are reinforced with hands-on exercises to nurture the student's skill in problem solving. New concepts and algorithms are framed by real-world context and established as part of the big picture introduced in an early chapter. A problem-solving strategy is employed in several chapters to equip students with an approach for new problems in pattern recognition. This text also points out common errors that a new player in pattern recognition may encounter, and fosters the ability for readers to find useful resources and independently solve a new pattern recognition task through various working examples. Students with an undergraduate understanding of mathematical analysis, linear algebra, and probability will be well prepared to master the concepts and mathematical analysis presented here.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: Cambridge University Press
• Erscheinungstermin: 19. November 2020
• Englisch
• ISBN-13: 9781108755191
• Artikelnr.: 66180991

Autorenporträt

Jianxin Wu is a professor in the Department of Computer Science and Technology and the School of Artificial Intelligence at Nanjing University, China. He received his B.S. and M.S. degrees in computer science from Nanjing University and his Ph.D. degree in computer science from the Georgia Institute of Technology. Professor Wu has served as an area chair for the conference on Computer Vision and Pattern Recognition (CVPR), the International Conference on Computer Vision (ICCV), and the AAAI Conference on Artificial Intelligence, and he is an associate editor for the Pattern Recognition journal. His research interests are computer vision and machine learning.

Inhaltsangabe

Preface
Notation
Part I. Introduction and Overview: 1. Introduction
2. Mathematical background
3. Overview of a pattern recognition system
4. Evaluation
Part II. Domain-Independent Feature Extraction: 5. Principal component analysis
6. Fisher's linear discriminant
Part III. Classifiers and Tools: 7. Support vector machines
8. Probabilistic methods
9. Distance metrics and data transformations
10. Information theory and decision trees
Part IV. Handling Diverse Data Formats: 11. Sparse and misaligned data
12. Hidden Markov model
Part V. Advanced Topics: 13. The normal distribution
14. The basic idea behind expectation-maximization
15. Convolutional neural networks
References
Index.