Kapitel/Beitrag aus dem Buch: Längle, T et al. 2013. OCM 2013 – Optical Characterization of Materials – conference proceedings.
Against the background of hyperspectral imaging this
paper evaluates a number of different machine learning based
classification methods in terms of their performance. All considered
methods offer relevance profiles that additionally provide
valuable information about the relevance of all acquired wavelengths
to get the obtained classification. This relevance profile
can be used to select appropriate wavelengths or wavelength
bands to customize data acquisition and analysis tailored to the
specific application at hand.
Backhaus A. & Seiffert U. 2013. Comprehensive, non-invasive, and quantitativemonitoring of the health and nutrition state ofcrop plants by means of hyperspectral imagingand computational intelligence based analysis. In: Längle, T et al (eds.), OCM 2013 – Optical Characterization of Materials – conference proceedings. Karlsruhe: KIT Scientific Publishing. DOI: https://doi.org/10.58895/ksp/1000032143-10
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Veröffentlicht am 6. März 2013