Fast phytoplankton classification from emission fluorescence spectra based on Self-Organizing Maps

被引:0
作者
Aymerich, Ismael F. [1 ]
Piera, Jaume [1 ,2 ]
Soria-Frisch, Aureli [3 ]
机构
[1] UTM, CSIC, Pg Maritim Barceloneta 37-49, E-08003 Barcelona, Spain
[2] UPC, Barcelona 08034, Spain
[3] UPF, Barcelona 08003, Spain
来源
OCEANS 2008, VOLS 1-4 | 2008年
关键词
ARTIFICIAL NEURAL-NETWORK; PATTERNS; COLOR;
D O I
暂无
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
Fluorescence spectroscopy is a powerful technique usually used to evaluate phytoplankton marine environments. In this study, a fast-technique for phytoplankton discrimination is presented based on the Self-Organizing Maps (SOM), evaluating its capability to achieve phytoplankton classification from its emission fluorescence spectra. The aim of this work is to reduce the acquisition time required for some of the existing techniques. Several cultures representing different algae groups were grown under the same conditions and their Emission spectra were measured every day. Finally, SOM analysis combined with derivative analysis was performed obtaining encouraging results.
引用
收藏
页码:896 / +
页数:2
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