The sugar dataset - A multimodal hyperspectral dataset for classification and research

Datacite citation style:
Melchert, Friedrich; Matros, A. (Andrea); Biehl, M. (Michael); Seiffert, U. (Udo) (2016): The sugar dataset - A multimodal hyperspectral dataset for classification and research. Version 1. 4TU.ResearchData. dataset.
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The sugar dataset is a multimodal hyperspectral dataset of sugar and sugar related substances. The substances that were used for the creation of dataset are: - Sugar Ester S170 - Sugar Ester S770 - Sugar Ester S1570 - Sugar Ester P1570 - D-Mannitol - D-Sorbitol - D-Glucose - D-Galactose - D-Fructose All of the substances were hyperspectrally recorded using different sensors, namely: - Canon EOS 70D - ASD FiledSpec 3 - Neo VNIR-1600 - Neo VNIR-1800 - Neo SWIR-320m-e - Neo SWIR-384 - Nuance Ex The different sensors cover different wavelength ranges as well as different wavelength resolutions. This creates a unique dataset, that not only takles the question of hyperspectral classification, but also enable the research on topics like high dimensional data exploration, sensor invariant classification and dimensionality reduction.
  • 2016-06-30 first online, published, posted
University of Groningen
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Fraunhofer Institute for Factory Operation and Automation IFF, Magdeburg, Germany;
Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany;
University of Groningen, Johann Bernoulli Institute for Mathematics and Computer Science, Groningen, The Netherlands


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