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Springer - A Probabilistic Theory of Pattern Recognition Book

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Description

Pattern recognition presents a significant challenge for scientists and engineers. This book from Springer provides a self-contained account of probabilistic techniques applied to the subject. As part of the Stochastic Modelling and Applied Probability series (Volume 31), it offers a wide-ranging account of the field. This text is designed to support researchers and graduate students as they navigate various approaches to pattern recognition through a probabilistic lens.

Key Features

This Springer publication provides a self-contained account of probabilistic techniques for pattern recognition.

The text serves as a comprehensive resource for researchers and graduate students studying the field.

Part of the Stochastic Modelling and Applied Probability series, volume 31.

Addresses the challenges of pattern recognition through various scientific and engineering approaches.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
22 November 2013
Listed Since
22 April 2014

Barcode

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