| Full text | |
| Author(s): |
Valerio Netto, Antonio
;
De Carvalho, Andre C. Ponce De Leon F.
Total Authors: 2
|
| Document type: | Journal article |
| Source: | INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE AND APPLICATIONS; v. 5, n. 3, p. 13-pg., 2005-09-01. |
| Abstract | |
The article presents the development of a Classifiers Combination based on machine learning techniques (Artificial Neural Networks, Support Vector Machines and C4.5 algorithm) which were able to increase the performance achieved by the Refractive Errors Measurement System (REMS) that analyzes Hartmann-Shack (HS) images from human eyes. The HS images are analyzed in order to extract relevant data for identification of refractive errors (myopia, hypermetropia and astigmatism). Those data are extracted using Gabor wavelets transform and afterwards, machine learning techniques are employed to carry out the image analysis. (AU) | |