Temat: fuzzy classifier - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Pattern recognition of sacroileitis with the use of multistage logic with a fuzzy loss function
Autorzy:: Burduk, R.
Powiązania:: https://bibliotekanauki.pl/articles/1965805.pdf
Data publikacji:: 2004
Wydawca:: Politechnika Gdańska
Tematy:: multistage classifier
sacroiletis
fuzzy loss function
k-nearest neighbor method
Opis:: The article describes the problem of pattern recognition of sacroileitis. Classification is based on a scheme of multistage recognition with a fuzzy loss function dependent on the node of the decision tree. Decision rules are based on k-nearest neighbors at particular internal nodes of the decision-tree. Paper presents influence of comparison fuzzy numbers on classifications results.
Źródło:: TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk; 2004, 8, 2; 217-221
1428-6394
Pojawia się w:: TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

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

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