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Semi-supervised graph-based band selection methods have shown satisfying performances to choose the valuable bands for the hyper spectral data classification in case of very limited labeled samples. However, the calculation of adjacency matrices based on all labeled and unlabeled samples requires a large computational load which can be unacceptable with the huge amounts of unlabeled samples available...
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