cff-version: 1.2.0
abstract: "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."
authors:
  - family-names: Melchert
    given-names: Friedrich
    orcid: "https://orcid.org/0000-0002-9145-2277"
  - family-names: Matros
    given-names: A. (Andrea)
  - family-names: Biehl
    given-names: M. (Michael)
  - family-names: Seiffert
    given-names: U. (Udo)
title: "The sugar dataset - A multimodal hyperspectral dataset for classification and research"
keywords:
version: 1
identifiers:
  - type: doi
    value: 10.4121/uuid:fad486b6-0dfb-4d23-8025-b24407a08698
license: 4TU General Terms of Use
date-released: 2016-06-30