Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
IEEE Transactions on Pattern Analysis and Machine Intelligence
Experiments in colour texture analysis
Pattern Recognition Letters
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Combining Pattern Classifiers: Methods and Algorithms
Combining Pattern Classifiers: Methods and Algorithms
Editorial: Hybrid learning machines
Neurocomputing
A First Study on the Use of Coevolutionary Algorithms for Instance and Feature Selection
HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems
Editorial: Hybrid intelligent algorithms and applications
Information Sciences: an International Journal
Dynamic and static weighting in classifier fusion
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part II
Designing fusers on the basis of discriminants – evolutionary and neural methods of training
HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part I
| Hi-index | 0.00 |
One objective for classifying pixels belonging to specific textures in natural images is to achieve the best performance in classification as possible. We propose a new unsupervised hybrid classifier. The base classifiers for hybridization are the Fuzzy Clustering and the parametric Bayesian, both supervised and selected by their well-tested performance, as reported in the literature. During the training phase we estimate the parameters of each classifier. During the decision phase we apply fuzzy aggregation operators for making the hybridization. The design of the unsupervised classifier from supervised base classifiers and the automatic computation of the final decision with fuzzy aggregation operations, make the main contributions of this paper.