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Found 3 papers, 2 papers with code
Deep Learning Driven Detection of Tsunami Related Internal GravityWaves: a path towards open-ocean natural hazards detection
We describe a framework leveraging slant total electron content (sTEC) from the VARION (Variometric Approach for Real-Time Ionosphere Observation) algorithm by Gramian Angular Difference Fields (from Computer Vision) and Convolutional Neural Networks (CNNs) to detect TIDs in near-real-time.
Detecting Anomalous Invoice Line Items in the Legal Case Lifecycle
Using machine learning, our goal is to demonstrate the current flaws of, and to explore improvements to, the legal invoice review process for invoices submitted by law firms to their corporate clients.
Detecting Spacecraft Anomalies Using LSTMs and Nonparametric Dynamic Thresholding
As spacecraft send back increasing amounts of telemetry data, improved anomaly detection systems are needed to lessen the monitoring burden placed on operations engineers and reduce operational risk.
