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arxiv: 2101.01154 · v1 · pith:BBEQ2IDT · submitted 2021-01-04 · cs.CV · cs.AI· cs.LG

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

Reviewed by Pithpith:BBEQ2IDTopen to challenge →

classification cs.CV cs.AIcs.LG
keywords datachangecontestcoverlandbaselinesdfc2021fusion
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We present simple algorithms for land cover change detection in the 2021 IEEE GRSS Data Fusion Contest. 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. See https://dfc2021.blob.core.windows.net/competition-data/dfc2021_index.txt for the data and https://github.com/calebrob6/dfc2021-msd-baseline for an implementation of these baselines.

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