A Neural Network for Classification of Chambers Arrangement in Foraminifera
A Neural Network for Classification of Chambers Arrangement in Foraminifera
复制标题
有孔虫腔室排列分类的神经网络
DOI：
10.1007/10983652_33
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发表时间：
2003
期刊：
影响因子：
--
通讯作者：
S. Amodio
中科院分区：
文献类型：
--
作者：
R. Marmo;S. Amodio
有孔虫是确定海相岩石地质时代的重要微体化石。图像分析技术被用来计算两组形状特征描述最常见的有孔虫壳的形状。一个k-最近邻和多层感知器分类器进行了比较室安排的自动分类。实验结果表明，87.1和97.1%的准确性，分别使用，k-近邻和多层感知器。
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.