Potential support vector machines for phytoplankton fluorescence spectra classification: comparison with self-organizing maps.
PublisherSARTI (Technological Development Centre of Remote Acquisition and Data processing Systems)
Rights accessOpen Access
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.
CitationAymerich, Ismael F. [et al.]. Potential support vector machines for phytoplankton fluorescence spectra classification: comparison with self-organizing maps.. "Instrumentation Viewpoint", 26 Abril 2010, núm. 8, p. 81.