Stand-Alone Vision Sensor Design Based on Fuzzy Associative Database
CRV '04 Proceedings of the 1st Canadian Conference on Computer and Robot Vision
Designing spectral sensitivity curves for use with Artificial Color
Pattern Recognition
Content-based image retrieval using associative memories
TELE-INFO'07 Proceedings of the 6th WSEAS Int. Conference on Telecommunications and Informatics
Restoring images with a multiscale neural network based technique
Proceedings of the 2008 ACM symposium on Applied computing
Fuzzy neural network models for multispectral image analysis
CSECS'06 Proceedings of the 5th WSEAS International Conference on Circuits, Systems, Electronics, Control & Signal Processing
An expert system for predicting aeration performance of weirs by using ANFIS
Expert Systems with Applications: An International Journal
Association-based image retrieval for automatic target recognition
AIKED'08 Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks
Hybrid learning-based neuro-fuzzy inference system: a new approach for system modeling
International Journal of Systems Science
Association-based image retrieval
WSEAS Transactions on Signal Processing
Expert Systems with Applications: An International Journal
Interval type-2 fuzzy membership function generation methods for pattern recognition
Information Sciences: an International Journal
Integrated Computer-Aided Engineering
Nucleus Segmentation and Recognition of Uterine Cervical Pap-Smears
RSFDGrC '07 Proceedings of the 11th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
Breast cancer diagnosis system based on wavelet analysis and fuzzy-neural
Expert Systems with Applications: An International Journal
Automatic machine vision calibration using statistical and neural network methods
Image and Vision Computing
Advances in Engineering Software
Using intelligent methods to predict air-demand ratio in venturi weirs
Advances in Engineering Software
Further study on camera position estimation from image by ANFIS
Artificial Life and Robotics
Knowledge elicitation for performance assessment in a computerized surgical training system
Applied Soft Computing
Diagnosing Breast Masses in Digital Mammography Using Feature Selection and Ensemble Methods
Journal of Medical Systems
Expert Systems with Applications: An International Journal
Automatic RNA virus classification using the Entropy-ANFIS method
Digital Signal Processing
Generation of neural networks using a genetic algorithm approach
International Journal of Bio-Inspired Computation
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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. 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 moreComputer Vision and Fuzzy-Neural Systems illuminates the state-of-the-art throughhands-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 IncludedContains extensive library of MATLAB command files, executable files for some useful programs, and test images from Kodak and Space Imaging. Author Biography: Dr. Arun D. Kulkarni is Professor of Computer Science at The University of Texas at Tyler, Tyler, Texas. His research interests include computer vision, fuzzy-neural systems, data mining, image processing, and artificial intelligence. He has authored a book and published more than 50 referred papers. His awards include the 1984 Fulbright Fellowship award and the 1997 NASA/ASSE Summer Faculty Fellowship. Dr. Kulkarni obtained his Ph.D. from the Indian Institute of Technology, Bombay, and was a post-doctoral fellow at Virginia Tech.