Time-warping enables RNN transfer learning across time scales in physical systems by rescaling time in pretrained LSTMs, matching accuracy of other methods with minimal parameter changes.
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A Fire Event Tracker (FET) algorithm performs spatio-temporal clustering on MTG-FCI active fire detections to enable consistent near-real-time and retrospective fire event monitoring.
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Time-Warping Recurrent Neural Networks for Transfer Learning
Time-warping enables RNN transfer learning across time scales in physical systems by rescaling time in pretrained LSTMs, matching accuracy of other methods with minimal parameter changes.
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Leveraging MTG-FCI fire observations for event-based fire behavior monitoring from near-real-time operation to seasonal analysis
A Fire Event Tracker (FET) algorithm performs spatio-temporal clustering on MTG-FCI active fire detections to enable consistent near-real-time and retrospective fire event monitoring.