- Tytuł:
- Membership function - ARTMAP neural networks
- Autorzy:
-
Sinčák, P.
Hric, M.
Vaščák, J. - Powiązania:
- https://bibliotekanauki.pl/articles/1931570.pdf
- Data publikacji:
- 2003
- Wydawca:
- Politechnika Gdańska
- Tematy:
-
pattern recognition principles
classifier design
classification accuracy assessment
contingency tables
backpropagation neural networks
fuzzy BP neural networks
ART and ARTMAP neural networks
modular neural networks
neural networks - Opis:
- The project deals with the application of computational intelligence (CI) tools for multispectral image classification. Pattern Recognition scheme is a global approach where the classification part is playing an important role to achieve the highest classification accuracy. Multispectral images are data mainly used in remote sensing and this kind of classification is very difficult to assess the accuracy of classification results. There is a feedback problem in adjusting the parts of pattern recognition scheme. Precise classification accuracy assessment is almost impossible to obtain, being an extremely laborious procedure. The paper presents simple neural networks for multispectral image classification, ARTMAP-like neural networks as more sophisticated tools for classification, and a modular approach to achieve the highest classification accuracy of multispectral images. There is a strong link to advances in computer technology, which gives much better conditions for modelling more sophisticated classifiers for multispectral images.
- Źródło:
-
TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk; 2003, 7, 1; 43-52
1428-6394 - Pojawia się w:
- TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk
- Dostawca treści:
- Biblioteka Nauki
Artykuł