The sugar dataset - A multimodal hyperspectral dataset for classification and research
datasetposted on 30.06.2016 by Friedrich Melchert, A. (Andrea) Matros, M. (Michael) Biehl, U. (Udo) Seiffert
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
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.