A weakly supervised framework that combines consensus labels from three global land-cover products with unsupervised spatial-visual regularization improves large-scale cropland mapping without manual labels.
Journal of Integrative Agriculture 17, 1915–1931.https://linkinghub.elsevier.com/retrieve/pii/S2095311917618598
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Weakly Supervised Framework Considering Multi-temporal Information for Large-scale Cropland Mapping with Satellite Imagery
A weakly supervised framework that combines consensus labels from three global land-cover products with unsupervised spatial-visual regularization improves large-scale cropland mapping without manual labels.