EVL graduate research assistant Landon Dyken under the supervision of Sidharth Kumar is recognized for the publication entitled “Enabling Fast and Accurate Crowdsourced Annotation for Elevation-Aware Flood Extent Mapping”. Mapping the extent of flood events is an important aspect of disaster management. In recent years, deep learning methods have evolved as an effective tool to label high-resolution imagery and provide necessary flood extent mappings quickly. These methods, though, require large amounts of annotated training data to create models that are accurate and robust to new flooded imagery. FloodTrace, a web-based application that enables effective crowdsourcing of flooded region annotation for machine learning applications, helps address these challenges.

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