A supervised BiLSTM improves dense event classification of offshore wind Sentinel-1 time series over the rule-based baseline (AUCEditSim 0.7853 to 0.8509), and the resulting labels expose regional deployment dynamics.
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Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series
A supervised BiLSTM improves dense event classification of offshore wind Sentinel-1 time series over the rule-based baseline (AUCEditSim 0.7853 to 0.8509), and the resulting labels expose regional deployment dynamics.