Pattern Recognition and Image Analysis
Gose, Earl
Pattern Recognition and Image Analysis - Noida Pearson Education India 2015
Pattern recognition is at the heart of applications ranging from the identification white blood cells to the selection of tax returns for auditing, from earthquake prediction to speech recognition. This book is An ideal introduction to pattern recognition for both higher level undergraduate and beginning graduate courses. The text provides extensive worked examples and realistic applications that have been thoroughly classroom-tested. Since images are often the input to pattern recognition systems, a survey of image processing theory is included,..covering techniques such as scene segmentation, Hough transforms,least squares, Eigenvector line fitting, and Fourier transforms. The following important aspect, of pattern recognition are also presented:
Probability theory
Statistical decision making, including Bayer' Theorem
Nonparametric decision making, including histograms Hierarchical and partitional clustering: the advantages and risks
Artificial neural networks—and how they work in real applications such as classifying sex from facial images.
Readers do not need.computer science expertise or mathematical background beyond elementary calculus.
9789332549791
Optical pattern recognition.
Image processing--Statistical methods.
Neural networks (Computer science)
006.42 GOS
Pattern Recognition and Image Analysis - Noida Pearson Education India 2015
Pattern recognition is at the heart of applications ranging from the identification white blood cells to the selection of tax returns for auditing, from earthquake prediction to speech recognition. This book is An ideal introduction to pattern recognition for both higher level undergraduate and beginning graduate courses. The text provides extensive worked examples and realistic applications that have been thoroughly classroom-tested. Since images are often the input to pattern recognition systems, a survey of image processing theory is included,..covering techniques such as scene segmentation, Hough transforms,least squares, Eigenvector line fitting, and Fourier transforms. The following important aspect, of pattern recognition are also presented:
Probability theory
Statistical decision making, including Bayer' Theorem
Nonparametric decision making, including histograms Hierarchical and partitional clustering: the advantages and risks
Artificial neural networks—and how they work in real applications such as classifying sex from facial images.
Readers do not need.computer science expertise or mathematical background beyond elementary calculus.
9789332549791
Optical pattern recognition.
Image processing--Statistical methods.
Neural networks (Computer science)
006.42 GOS
