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

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.