Spectral band permutation pretraining with curriculum learning reaches R2=0.9456 for EnMAP soil organic carbon estimation, beating the tested SSL and supervised baselines.
Using enmap satellite and machine learning for soil organic carbon assessment: A case study in semi-arid region
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SpecBPP: A Self-Supervised Learning Approach for Hyperspectral Representation and Soil Organic Carbon Estimation
Spectral band permutation pretraining with curriculum learning reaches R2=0.9456 for EnMAP soil organic carbon estimation, beating the tested SSL and supervised baselines.