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

?titleThe sugar dataset - A multimodal hyperspectral dataset for classification and research
?creatororcidMelchert, F. (Friedrich)
?creatorMatros, A. (Andrea)
?creatorBiehl, M. (Michael)
?creatorSeiffert, U. (Udo)
?contributorFraunhofer Institute for Factory Operation and Automation IFF, Magdeburg, Germany
?contributorLeibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
?contributorUniversity of Groningen, Johann Bernoulli Institute for Mathematics and Computer Science, Groningen, The Netherlands
?date accepted2016-06-30
?date created2016-03-14 through 2016-06-22
?date published2016
?description
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.
?languageen
?publisherUniversity of Groningen
?subjectClassification ● Dimensionality Reduction ● Hyperspectral data ● Model invariant classification ● Model Transfer
? ▲ in collection
?related publicationnew windowThe sugar dataset: A multimodal hyperspectral dataset for classification and research. (MIWOCI 2016)
DATA
+bag-info
+contents of this dataset, 17 files
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