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Found 6 papers, 2 papers with code
Open-source data pipeline for street-view images: a case study on community mobility during COVID-19 pandemic
Street View Images (SVI) are a common source of valuable data for researchers.
Data-driven sparse polynomial chaos expansion for models with dependent inputs
Recently, different approaches have been proposed for models with dependent inputs to expand the use of PCEs to more real-world applications.
Post-Hurricane Damage Assessment Using Satellite Imagery and Geolocation Features
In this work, a creative choice of the geolocation features was made to provide extra information to the imagery features, but it is up to the users to decide which other features can be included to model the physical behavior of the events, depending on their domain knowledge and the type of disaster.
Splitting Gaussian Process Regression for Streaming Data
The algorithm is shown to have superior time and space complexity to existing methods, and its sequential nature permits application to streaming data.
Benchmark Dataset for Automatic Damaged Building Detection from Post-Hurricane Remotely Sensed Imagery
Rapid damage assessment is of crucial importance to emergency responders during hurricane events, however, the evaluation process is often slow, labor-intensive, costly, and error-prone.
Building Damage Annotation on Post-Hurricane Satellite Imagery Based on Convolutional Neural Networks
In this paper, we propose to improve the efficiency of building damage assessment by applying image classification algorithms to post-hurricane satellite imagery.
