TY - DATA
T1 - The sugar dataset - A multimodal hyperspectral dataset for classification and research
PY - 2016/06/30
AU - Friedrich Melchert
AU - A. (Andrea) Matros
AU - M. (Michael) Biehl
AU - U. (Udo) Seiffert
UR - https://data.4tu.nl/articles/dataset/The_sugar_dataset_-_A_multimodal_hyperspectral_dataset_for_classification_and_research/12719294/1
DO - 10.4121/uuid:fad486b6-0dfb-4d23-8025-b24407a08698
KW - Classification
KW - Dimensionality Reduction
KW - Hyperspectral data
KW - Model Transfer
KW - Model invariant classification
N2 - 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.
ER -