Abstract
This paper introduces a new classifier, that is based on fuzzy-integration schemes controlled by a genetic optimisation procedure. Two different types of integration are proposed here, and are validated by experiments on real data sets of biological cells.The performance of our classifier is tested against a feed-forward neural network and a Support Vector Machine. Results show the good performance and robustness of the integrated classifier strategies.
Lingua originale | English |
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pagine (da-a) | 411-420 |
Numero di pagine | 10 |
Rivista | Pattern Recognition Letters |
Volume | 26 |
Stato di pubblicazione | Published - 2005 |
All Science Journal Classification (ASJC) codes
- Software
- Signal Processing
- Computer Vision and Pattern Recognition
- Artificial Intelligence