Markov Models for Pattern Recognition From Theory to Applications /

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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, demonstrat...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Fink, Gernot A. (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: London : Springer London : Imprint: Springer, 2014.
Edición:2nd ed. 2014.
Colección:Advances in Computer Vision and Pattern Recognition,
Temas:
Pattern recognition systems.
Computer vision.
Natural language processing (Computer science).
Artificial intelligence.
Automated Pattern Recognition.
Computer Vision.
Natural Language Processing (NLP).
Artificial Intelligence.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • 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.

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