DEM Super-Resolution with EfficientNetV2 (Papers Track)

Bekir Z Demiray (University of Iowa); Muhammed A Sit (The University of Iowa); Ibrahim Demir (The University of Iowa)

Paper PDF Slides PDF Recorded Talk NeurIPS 2021 Poster Cite
Computer Vision & Remote Sensing Disaster Management and Relief Earth Observation & Monitoring

Abstract

Efficient climate change monitoring and modeling rely on high-quality geospatial and environmental datasets. Due to limitations in technical capabilities or resources, the acquisition of high-quality data for many environmental disciplines is costly. Digital Elevation Model (DEM) datasets are such examples whereas their low-resolution versions are widely available, high-resolution ones are scarce. In an effort to rectify this problem, we propose and assess an EfficientNetV2 based model. The proposed model increases the spatial resolution of DEMs up to 16 times without additional information.

Recorded Talk (direct link)

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