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Markov Models for Pattern Recognition : From Theory to Applications
Overview of attention for book
Table of Contents
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Book Overview
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Chapter 1
Introduction
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Chapter 2
Application Areas
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Chapter 3
Foundations of Mathematical Statistics
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Chapter 4
Vector Quantization and Mixture Estimation
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Chapter 5
Hidden Markov Models
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Chapter 6
n -Gram Models
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Chapter 7
Computations with Probabilities
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Chapter 8
Configuration of Hidden Markov Models
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Chapter 9
Robust Parameter Estimation
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Chapter 10
Efficient Model Evaluation
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Chapter 11
Model Adaptation
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Chapter 12
Integrated Search Methods
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Chapter 13
Speech Recognition
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Chapter 14
Handwriting Recognition
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Chapter 15
Analysis of Biological Sequences
Overall attention for this book and its chapters
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Mentioned by
syllabi
1
institution with syllabi
Citations
dimensions_citation
64
Dimensions
Readers on
mendeley
171
Mendeley
Book overview
1. Introduction
2. Application Areas
3. Foundations of Mathematical Statistics
4. Vector Quantization and Mixture Estimation
5. Hidden Markov Models
6. n -Gram Models
7. Computations with Probabilities
8. Configuration of Hidden Markov Models
9. Robust Parameter Estimation
10. Efficient Model Evaluation
11. Model Adaptation
12. Integrated Search Methods
13. Speech Recognition
14. Handwriting Recognition
15. Analysis of Biological Sequences
Summary
Syllabi
Dimensions citations
This data is correct as of December 2015 - for more up to date information, please visit
https://opensyllabus.org/
So far, Altmetric has seen this research output assigned in
1
syllabus from an institution on Open Syllabus Project.
Institution
Syllabi count
Course subject areas covered
Old Dominion University
1
Business, Agriculture