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.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.IV 1years
2019 1verdicts
REJECT 1representative citing papers
citing papers explorer
-
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.