Fuzzy logic and neural networks for computer vision.
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Fuzzy logic and neural networks for computer vision.

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Published by IEEE in Piscataway, NJ .
Written in English


Book details:

Edition Notes

ContributionsKeller, James.
ID Numbers
Open LibraryOL20930495M
ISBN 100780321960

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The theory behind neural networks and fuzzy logic is not explained well with quite a bit of unexplained jargin. The C++ code is usable but not well done. I felt that the C++ code should be secondary to the explanations anyway, but it would have been nice to see good by: A variety of fuzzy-neural network models have been used in computer vision. This book deals with the topic of fuzzy-neural systems as applied to computer vision. The book provides exercises at the end of each chapter, and it can be used as a textbook for a course in computer vision at senior undergraduate or master degree level. artificial neural networks fuzzy logic machine learning computer vision evolutionary algorithms genetic algorithms algorithmic game theory and mechanism design semantics and reasoning probabilistic representations artificial intelligence bio-inspired approaches reinforcement learning multi-task learning pattern recognition differential.   Fuzzy Logic and Neural Network 1. By Mrs. Shimi S.L Assistant Professor,EE NITTTR, Chandigarh Fuzzy Logic using MATLAB 2. The term "fuzzy logic" was introduced with the proposal of fuzzy set theory by Lotfi A. Zadeh.

Request PDF | Computer Vision and Fuzzy-Neural Systems | From the Publisher: New computer vision techniques based on neural networks, fuzzy inference systems, and fuzzy-neural network models. Useful for courses in computer vision, pattern recognition, or image processing, this book presents the field's comprehensive tutorial and reference to apply fuzzy-neural systems to . C++ Neural Networks and Fuzzy Logic (V.B. Rao) This book explains the theory of neural networks and provides illustrative examples in C++ that the reader can use as a basis for further experimentation. game playing, natural language understanding, computer vision, speech recognition, and robotics. From the Publisher: 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.

Computer vision and fuzzy-neural systems. Upper Saddle River, NJ: Prentice Hall PTR, © (OCoLC) Online version: Kulkarni, Arun D., Computer vision and fuzzy-neural systems. Upper Saddle River, NJ: Prentice Hall PTR, © (OCoLC) Document Type: Book: All Authors / Contributors: Arun D Kulkarni. probabilistic approaches to neural networks (especially classication networks) and fuzzy logic systems, and Bayesian reasoning. A.P. Papli nski´ 1 1 Neuro-Fuzzy Comp. Ch. 1 Neuro-Fuzzy systems We may say that neural networks and fuzzy systems try to File Size: KB. 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. Fuzzy Logic and Intelligent Systems reflects the most recent developments in neural networks and fuzzy logic, and their application in intelligent systems. In addition, the balance between theoretical work and applications makes the book suitable for both researchers and engineers, as .