Evolutionary Learning of Classifiers for Disk Discrimination
| Autor: | Leehter Yao, Meng-Seng Wu, Kuei-Sung Weng |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
Physics
business.industry Supervised learning ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Compact disc Laser Ellipsoid Computer Science Applications law.invention ComputingMethodologies_PATTERNRECOGNITION Control and Systems Engineering law Data_FILES Computer vision Astrophysics::Earth and Planetary Astrophysics Disk laser Artificial intelligence Electrical and Electronic Engineering Adaptive optics business Optical disc Classifier (UML) Astrophysics::Galaxy Astrophysics |
| Zdroj: | IEEE/ASME Transactions on Mechatronics. 20:3194-3203 |
| ISSN: | 1941-014X 1083-4435 |
| Popis: | A novel disk discrimination approach with two levels of classification is proposed. The optical pickup head is controlled to emit the digital versatile disk laser followed by the compact disk laser during the process of being pulled in from the neutral position toward the optical disk. Four features are measured and analyzed based on the reflected signals from the optical disk. Two levels of classifications are designed for the disk discrimination using these four features. A supervised learning approach based on the evolutionary ellipsoid classification algorithm is utilized to learn the classifiers and optimize the classifier parameterizations. Six different disk types have been successfully discriminated using the proposed approach. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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