Foraminifera are very important microfossils to determine geological age of marine rocks. Image analysis techniques are used to compute two set of shape features describing the shape of the most common foraminifera shells. A k-nearest neighbor and a multiplayer perceptron classifiers are compared for automated classification of the chambers arrangement. Experimental results show 87.1 and 97.1% of accuracy using, respectively, k-nearest neighbor and multiplayer perceptron.
A Neural Network for classification of chambers arrangement in foraminifera
S AMODIO
2006
Abstract
Foraminifera are very important microfossils to determine geological age of marine rocks. Image analysis techniques are used to compute two set of shape features describing the shape of the most common foraminifera shells. A k-nearest neighbor and a multiplayer perceptron classifiers are compared for automated classification of the chambers arrangement. Experimental results show 87.1 and 97.1% of accuracy using, respectively, k-nearest neighbor and multiplayer perceptron.File in questo prodotto:
Non ci sono file associati a questo prodotto.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
