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Fuzzy: Neural Systems for Image Understanding
 
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Fuzzy: Neural Systems for Image Understanding (Hardcover)

by Arun D. Kulkarni (Author)
4.0 out of 5 stars See all reviews (1 customer review)

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Product details

  • Hardcover: 504 pages
  • Publisher: Prentice Hall; Har/Cdr edition (16 May 2001)
  • Language English
  • ISBN-10: 0135705991
  • ISBN-13: 978-0135705995
  • Product Dimensions: 24.2 x 18.5 x 3 cm
  • Average Customer Review: 4.0 out of 5 stars See all reviews (1 customer review)
  • Amazon.co.uk Sales Rank: 2,585,740 in Books (See Bestsellers in Books)
  • See Complete Table of Contents

Product Description

Product Description

For courses in computer vision, pattern recognition, or image processing at the senior undergraduate level or first year graduate level.

This essential resource brings together the field's latest research and applications, presenting the field's first comprehensive tutorial and reference to apply fuzzy-neural systems to computer vision applications, such as remote sensing, medical image analysis, data compression, fingerprint analysis, and character recognition. Reflects most recent trends in computer vision and provides algorithms with practical examples.



From the Back Cover

  • New computer vision techniques based on neural networks, fuzzy inference systems, and fuzzy-neural network models
  • Detailed tutorials, hands-on exercises, real-world examples, and proven algorithms

CD-ROM: code libraries for the MATLAB neural network, fuzzy logic, and image processing toolboxes, test images from Kodak and Space Imaging, and more.

The first complete guide to applying fuzzy-neural systems in computer vision.

Recent advances in neural networks and fuzzy logic are transforming the field of computer vision, making it possible for computer vision applications to learn much as the brain does, and to handle imprecise visual data far more effectively. Now, Dr. Arun D. Kulkarni brings together the field's latest research and applications, presenting the field's first comprehensive tutorial and reference.

Kulkarni starts by reviewing the fundamentals of computer vision, and the stages of a computer vision system. He shows how these stages have traditionally been implemented via statistical techniques; then introduces approaches that incorporate neural networks, fuzzy inference systems, and fuzzy-neural network models. Coverage includes:

  • Preprocessing techniques such as radiometric or geometric corrections
  • Feature extraction, supervised and unsupervised classification, associative memories, and other techniques for improving accuracy and performance
  • Key computer vision applications: remote sensing, medical imaging, compression, data mining, character recognition, stereovision, and more

Computer Vision and Fuzzy-Neural Systems illuminates the state-of-the-art through hands-on exercises, real-world examples, and proven algorithms. It's an essential resource for every engineer, scientist, and programmer working in computer vision and a wide range of related fields. It can also be used as a textbook for undergraduate- or graduate-level courses in computer vision.

CD-ROM Included

Contains extensive library of MATLAB command files, executable files for some useful programs, and test images from Kodak and Space Imaging.



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1 of 1 people found the following review helpful:
4.0 out of 5 stars Comprehensive but expensive, 16 Jul 2001
By A Customer
The style is very academic, and the book is therefore more suited to graduate or post-graduate studies than casual reading. However, it is very comprehensive and, despite the title, covers much more than artificial neural network and fuzzy system classification - there is a fair amount of coverage and mathematics for more "traditional" forms of pattern analysis.

I have only two criticisms: the first is the price! The second is that there is a bit too much repetition of the basics - virtually identical background information presented in several places - and possibly not enough reinforcement of more complex material.

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