Markov Models for Pattern Recognition (Record no. 57511)
[ view plain ]
| 000 -LEADER | |
|---|---|
| fixed length control field | 04189nam a22005415i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-1-4471-6308-4 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20200421112223.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 140114s2014 xxk| s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9781447163084 |
| -- | 978-1-4471-6308-4 |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 006.4 |
| 100 1# - AUTHOR NAME | |
| Author | Fink, Gernot A. |
| 245 10 - TITLE STATEMENT | |
| Title | Markov Models for Pattern Recognition |
| Sub Title | From Theory to Applications / |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 2nd ed. 2014. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | XIII, 276 p. 45 illus. |
| 490 1# - SERIES STATEMENT | |
| Series statement | Advances in Computer Vision and Pattern Recognition, |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Remark 2 | Introduction -- Application Areas -- Part I: Theory -- Foundations of Mathematical Statistics -- Vector Quantization and Mixture Estimation -- Hidden Markov Models -- N-Gram Models -- Part II: Practice -- Computations with Probabilities -- Configuration of Hidden Markov Models -- Robust Parameter Estimation -- Efficient Model Evaluation -- Model Adaptation -- Integrated Search Methods -- Part III: Systems -- Speech Recognition -- Handwriting Recognition -- Analysis of Biological Sequences. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | Markov models are extremely useful as a general, widely applicable tool for many areas in statistical pattern recognition. This unique text/reference places the formalism of Markov chain and hidden Markov models at the very center of its examination of current pattern recognition systems, demonstrating how the models can be used in a range of different applications. Thoroughly revised and expanded, this new edition now includes a more detailed treatment of the EM algorithm, a description of an efficient approximate Viterbi-training procedure, a theoretical derivation of the perplexity measure, and coverage of multi-pass decoding based on n-best search. Supporting the discussion of the theoretical foundations of Markov modeling, special emphasis is also placed on practical algorithmic solutions. Topics and features: Introduces the formal framework for Markov models, describing hidden Markov models and Markov chain models, also known as n-gram models Covers the robust handling of probability quantities, which are omnipresent when dealing with these statistical methods Presents methods for the configuration of hidden Markov models for specific application areas, explaining the estimation of the model parameters Describes important methods for efficient processing of Markov models, and the adaptation of the models to different tasks Examines algorithms for searching within the complex solution spaces that result from the joint application of Markov chain and hidden Markov models Reviews key applications of Markov models in automatic speech recognition, character and handwriting recognition, and the analysis of biological sequences Researchers, practitioners, and graduate students of pattern recognition will all find this book to be invaluable in aiding their understanding of the application of statistical methods in this area. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | http://dx.doi.org/10.1007/978-1-4471-6308-4 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | London : |
| -- | Springer London : |
| -- | Imprint: Springer, |
| -- | 2014. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
| -- | cr |
| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
| -- | |
| -- | rda |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer science. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Artificial intelligence. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computational linguistics. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Image processing. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Pattern recognition. |
| 650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer Science. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Pattern Recognition. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Image Processing and Computer Vision. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Language Translation and Linguistics. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Artificial Intelligence (incl. Robotics). |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| -- | 2191-6586 |
| 912 ## - | |
| -- | ZDB-2-SCS |
No items available.