Team Fundator: Weighted UNet ensembles with enhanced datasets

Authors

  • Lars Martin Hodne Norconsult Informasjonssystemer
  • Eivind Hovdegård Furdal Norconsult Informasjonssystemer

DOI:

https://doi.org/10.5617/nmi.9992

Keywords:

semantic segmentation, remote sensing, MapAI

Abstract

The 2022 MapAI: Precision in Building Segmentation competition has invited participants to develop systems which segment buildings in orthophotos. In this paper, we present our winning submission for the competition. Submissions are ranked based on the mean of two metrics: Intersection over Union (IoU) and Boundary Intersection over Union (BIoU). The competition evaluates these metrics on two separate tasks with RGB and RGB-Z images, respectively. In our solution, we incorporate heterogeneous, weighted U-Net ensembles, multiple extensions of the training data, and area-based post-processing of predictions to achieve leading results on the the test and validation data, achieving a score of 0.7635 and 0.9266, respectively.

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Published

2023-03-27

Issue

Section

NMI Challenge