High-resolution land cover change from low-resolution labels: Simple baselines for the 2021 IEEE GRSS Data Fusion Contest

Malkin, Nikolay, Robinson, Caleb, Jojic, Nebojsa

arXiv.org Artificial Intelligence 

The task of the contest is to create high-resolution (1m / pixel) land cover change maps of a study area in Maryland, USA, given multi-resolution imagery and label data. We study several baseline models for this task and discuss directions for further research.

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