New-application report: CNN and ConvLSTM networks trained on StaMPS labels select persistent scatterer pixels in Sentinel-1 interferograms, with reported validation accuracy of 93.50% for the LSTM variant.
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Deep learning networks for selection of persistent scatterer pixels in multi-temporal SAR interferometric processing
New-application report: CNN and ConvLSTM networks trained on StaMPS labels select persistent scatterer pixels in Sentinel-1 interferograms, with reported validation accuracy of 93.50% for the LSTM variant.