Open AccessBook
Fuzzy Mathematical Approach to Pattern Recognition
TLDR
Results of investigations, both experimental and theoretical, are presented into the effectiveness of fuzzy algorithms as classification tools in some problems concerned with the field of pattern recognition and image processing.Abstract:
This book aims to present results of investigations, both experimental and theoretical, into the effectiveness of fuzzy algorithms as classification tools in some problems concerned with the field of pattern recognition and image processing. Compares results to those obtained with statistical classification techniques.read more
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Journal ArticleDOI
A review on image segmentation techniques
Nikhil R. Pal,Sankar K. Pal +1 more
TL;DR: Attempts have been made to cover both fuzzy and non-fuzzy techniques including color image segmentation and neural network based approaches, which addresses the issue of quantitative evaluation of segmentation results.
Book
Artificial Neural Networks
TL;DR: artificial neural networks, artificial neural networks , مرکز فناوری اطلاعات و اصاع رسانی, کδاوρزی
Journal ArticleDOI
Learning multi-label scene classification
TL;DR: A framework to handle semantic scene classification, where a natural scene may contain multiple objects such that the scene can be described by multiple class labels, is presented and appears to generalize to other classification problems of the same nature.
Journal ArticleDOI
A comparison of neural network and fuzzy clustering techniques in segmenting magnetic resonance images of the brain
Lawrence O. Hall,A. Bensaid,Laurence P. Clarke,R.P. Velthuizen,Martin S. Silbiger,James C. Bezdek +5 more
TL;DR: For a more complex segmentation problem with tumor/edema or cerebrospinal fluid boundary, inconsistency in rating among experts was observed, with fuzzy c-means approaches being slightly preferred over feedforward cascade correlation results.
Journal ArticleDOI
Entropy, distance measure and similarity measure of fuzzy sets and their relations
TL;DR: The axiom definitions of entropy, distance measure and similarity measure of fuzzy sets are systematically given and basic relations between these measures are discussed.