Fuzzy sets in pattern recognition: Accomplishments and challenges
Fuzzy Sets and SystemsPublished 1 September 1997
Witold Pedrycz
Citations39
SJR quartileQ1
SJR score0.75
SNIP1.25
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
The role that fuzzy sets play in pattern recognition is identified and the main conceptual and algorithmic challenges are outlined.
Abstract
We identify and discuss a role that fuzzy sets play in pattern recognition. The main conceptual and algorithmic challenges are outlined. Highlighted are also some future trends.
Keywords
Computer Science
Pattern classification and scene analysis
12,643 Citations1973Richard O. Duda, Peter E. Hart
Fuzzy models for pattern recognition
825 Citations1994James C. Bezdek, Sankar K. Pal
The basic structure of fuzzy sets theory as it applies to the major problems encountered in the design of a pattern recognition system is described.
Information SciencesNumerical methods for fuzzy clustering
558 Citations1970Enrique H. Ruspini
The bulk of this paper is concerned with numerical techniques useful in the solution of numerical problems related to fuzzy clustering and partitions in more than two sets.
Journal of Mathematical Analysis and ApplicationsAbstraction and pattern classification
424 Citations1966Richard Bellman, Robert E. Kalaba +1 more
A general framework for the treatment of pattern-recognition problems is discussed, including the notion of a 'fuzzy' set and how this may be employed in a sequential experimental procedure to ascertain whether a symbol is a member of a particular set or not.
Pattern RecognitionFuzzy sets in pattern recognition: Methodology and methods
360 Citations1990Witold Pedrycz
A state-of-the-art of methodology and algorithms of fuzzy sets in the field of pattern recognition and clustering techniques are discussed and a problem of cluster validity expressed in terms of clustering indices is addressed.
Fuzzy Sets and SystemsFuzzy sets engineering
241 Citations1996
Fuzzy Sets Engineering presents the genuine essence of engineering of fuzzy sets in a top-down fashion, with general methodology followed by specific domains which rely strongly on the methodological foundations.
Pattern Recognition LettersAlgorithms of fuzzy clustering with partial supervision
147 Citations1985Witold Pedrycz
Methods of fuzzy clustering based minimization of a scalar performance index with the aid of some labelled patterns and some modifications of the performance index that take into account the results of partial supervision are proposed.
IEEE Transactions on Fuzzy SystemsA parametric model for fusing heterogeneous fuzzy data
127 Citations1996Richard J. Hathaway, James C. Bezdek +1 more
This work uses a small set of artificial data to illustrate how problems as diverse as feature analysis, clustering, cluster validity, and prototype classifier design can all be formulated and attacked with standard methods once the data are converted to the generalized coordinates of the model.
Fuzzy Sets in Pattern Recognition
46 Citations1987Hans-Jürgen Zimmermann
Fuzzy Set Theory is concerned with non-dichotomous structures, i.e., with situations which are not of the either-or-structure, which cannot be characterized by black- or- white, by true-or’false, by certain-Or-impossible.