Paddy Rice Mapping using Deep ResU-Net CNN Segmentation

doi: 10.4121/21764192.v1
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/21764192
Datacite citation style:
ONOJEGHUO, ALEX (2022): Paddy Rice Mapping using Deep ResU-Net CNN Segmentation. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/21764192.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset
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Alberta, Canada
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The main objective of this study was to develop a workflow for paddy rice field mapping using a combination of high spatial and temporal optical and radar satellite data in a deep-learning residual CNN model.

history
  • 2022-12-28 first online, published, posted
publisher
4TU.ResearchData
format
Acrobat pdf
organizations
Jolexy Environmental Services Limited

DATA

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