Potential support vector machines for phytoplankton fluorescence spectra classification: comparison with self-organizing maps.
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Evaluation of phytoplankton communities is an important task to characterize
marine environments. Fluorescence spectroscopy is a powerful technique
usually used for this goal. This study presents a comparison between two different
techniques for fast phytoplankton discrimination: Self-Organizing Maps (SOM) and
Potential Support Vector Machines (P-SVM), evaluating its capability to achieve
phytoplankton classification from its fluorescence spectra.
marine environments. Fluorescence spectroscopy is a powerful technique
usually used for this goal. This study presents a comparison between two different
techniques for fast phytoplankton discrimination: Self-Organizing Maps (SOM) and
Potential Support Vector Machines (P-SVM), evaluating its capability to achieve
phytoplankton classification from its fluorescence spectra.
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Aymerich, Ismael F. et al. “Potential support vector machines for phytoplankton fluorescence spectra classification: comparison with self-organizing maps”. Instrumentation viewpoint, no. 8, https://raco.cat/index.php/Instrumentation/article/view/196487.
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