Paper Info
Title
Evolutionary fuzzy clustering and functional modular neural network-based human recognition.
Abstract
Computational intelligence shows its ability for solving many real-world problems efficiently. Synergism of fuzzy logic, evolutionary computation, and neural network can lead to development of a computational efficient and performance-rich system. In this paper, we propose a new approach for solving the human recognition problem that is the fusion of evolutionary fuzzy clustering and functional modular neural networks (FMNN). Evolutionary searching technique is applied for finding the optimal number of clusters that are generated through fuzzy clustering. The functional modular neural network has been used for recognition process that is evaluated with the help of integration based on combining the outcomes of FMNN. Performance of the proposed technique has been empirically evaluated and analyzed with the help of different parameters.
Year
DOI
Venue
2013
10.1007/s00521-012-0973-7
Neural Computing and Applications
Keywords
DocType
Volume
Evolutionary search, Fuzzy clustering, Functional modular neural network, Biometrics, Face, Iris, Pattern recognition
Journal
22
Issue
ISSN
Citations 
Supplement-1
1433-3058
4
PageRank 
References 
Authors
0.47
19
3
Name
Order
Citations
PageRank
Vivek Srivastava1878.66
Bipin K. Tripathi2194.08
Vinay K. Pathak3295.20