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Erschienen in:
2019 | OriginalPaper | Buchkapitel
7. Bayesian Classification
verfasst von : Dr. Dengsheng Zhang
Erschienen in: Fundamentals of Image Data Mining
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Abstract
This chapter covers the first of four image classification methods in the book. It begins with a brief introduction of Bayesian theorem and demonstrates how Bayesian theorem works using two examples. The rest of the chapter focuses on applications of Bayesian theorem on image classification. It begins with describing how images can be classified using a simple Naïve Bayesian classifier and its variants. The NB methods give readers the opportunity to relate image data with Bayesian theorem before contacting with other sophisticated Bayesian methods. After these preparations, three more powerful and nonparametric Bayesian methods are described in algorithmic forms and illustrations. In the next, more advanced methods such as parametric method and Gaussian process are discussed with illustrations.