Multiclass Mineral Recognition Using Similarity Features and Ensembles of Pair-Wise Classifiers
Yükleniyor...
Dosyalar
Tarih
2010
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
SPRINGER-VERLAG BERLIN
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Mineral determination is a basis of the petrography Automatic mineral classification based on digital image, analysis is getting very popular To improve classification accuracy we consider similarity features. complex one stage classfiers and two-stage classifiers based on simple pair-wise classification algorithms Results show that employment of two-stage classifieis with proper parameters or K class single layer perceptron are good choices for mineral classification Similarity features with properly selected parameters allow obtaining non-lineal decision boundaries and lead to sizeable decrease in classification error rate
Açıklama
23rd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems -- JUN 01-04, 2010 -- Cordoba, SPAIN
Anahtar Kelimeler
Mincial Classification, Single Layer Perception, Support Vectors, Two Stage Classifiers, Similarity Features
Kaynak
Trends in Applied Intelligent Systems, PT II, Proceedings
WoS Q Değeri
N/A
Scopus Q Değeri
Q3
Cilt
6097
Sayı
Künye
Kybartas, R., Baykan, N. A., Yılmaz, N., Raudys, S., (2010). Multiclass Mineral Recognition Using Similarity Features and Ensembles of Pair-Wise Classifiers. Lecture Notes in Artificial Intelligence, 6097, 47-56.
