| 书目名称 | Markov Models for Pattern Recognition |
| 副标题 | From Theory to Appli |
| 编辑 | Gernot A. Fink |
| 视频video | |
| 概述 | Thoroughly revised, updated and expanded new edition.Examines pattern recognition systems from the perspective of Markov models, demonstrating how the models can be used in a range of applications.Pla |
| 丛书名称 | Advances in Computer Vision and Pattern Recognition |
| 图书封面 |  |
| 描述 | This thoroughly revised and expanded 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. Features: introduces the formal framework for Markov models; covers the robust handling of probability quantities; presents methods for the configuration of hidden Markov models for specific application areas; 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. |
| 出版日期 | Textbook 2014Latest edition |
| 关键词 | Handwriting Recognition; Markov-Models; Pattern Recognition; Speech Recognition |
| 版次 | 2 |
| doi | https://doi.org/10.1007/978-1-4471-6308-4 |
| isbn_softcover | 978-1-4471-7133-1 |
| isbn_ebook | 978-1-4471-6308-4Series ISSN 2191-6586 Series E-ISSN 2191-6594 |
| issn_series | 2191-6586 |
| copyright | Springer-Verlag London 2014 |
发表于 2025-3-21 18:47:23
