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A Textbook On Pattern Recognition
Presents both classical and current theoretical foundation of pattern recognition and practice of supervised, unsupervised and reinforces learning to build a complete background of professionals and engineering students.
Every pattern of the image and design cycles has been discussed in detail through illustrative examples and applications. The very latest method are incorporated in this text book including k-mean clustering, k-nearest neighborhood methods etc.
The information is clearly presented and illustrated by many examples and applications and is designed for use as a text for course in pattern recognition for both undergraduate and post graduate engineering students.
Every pattern of the image and design cycles has been discussed in detail through illustrative examples and applications. The very latest method are incorporated in this text book including k-mean clustering, k-nearest neighborhood methods etc.
The information is clearly presented and illustrated by many examples and applications and is designed for use as a text for course in pattern recognition for both undergraduate and post graduate engineering students.
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