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Engineering deep learning methods on automatic detection of damage in infrastructure due to extreme events
In the third and fourth studies, end-to-end networks are developed and tested as a new solution to directly detect cracks and spalling in the image collections of recent large earthquakes.
Deep Transformer Networks for Time Series Classification: The NPP Safety Case
An advanced temporal neural network referred to as the Transformer is used within a supervised learning fashion to model the time-dependent NPP simulation data and to infer whether a given sequence of events leads to core damage or not.
Map-Based Temporally Consistent Geolocalization through Learning Motion Trajectories
The experiments show that the motion trajectories can be learned by training an recurrent neural network, and temporally consistent geolocation can be predicted with both of the proposed strategies.
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