Abstract:<div>Satellite
image time series (SITS)
classification is a major research topic in remote sensing and is relevant for
a wide range of applications. Deep learning approaches have been commonly employed
for SITS classification and have provided state-of-the-art performance. However,
deep learning methods suffer from overfitting when labeled data is scarce. To address
this problem, we propose a novel self-supervised pre-training scheme to initialize
a Transformer-based network by utilizing large-scale unla… Show more
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