78 citations · 253 across the 56 of their papers we have counts for
7 papers · 1 filter
GeoFormer: A Multi-Polygon Segmentation Transformer
Maxim Khomiakov, Michael Riis Andersen, Jes Frellsen
In remote sensing there exists a common need for learning scale invariant shapes of objects like buildings. Prior works relies on tweaking multiple loss functions to convert segmen…
Navigating Uncertainty in Medical Image Segmentation
Kilian Zepf, Jes Frellsen, Aasa Feragen
We address the selection and evaluation of uncertain segmentation methods in medical imaging and present two case studies: prostate segmentation, illustrating that for minimal anno…
Polygonizer: An auto-regressive building delineator
Maxim Khomiakov, Michael Riis Andersen, Jes Frellsen
In geospatial planning, it is often essential to represent objects in a vectorized format, as this format easily translates to downstream tasks such as web development, graphics, o…
That Label's Got Style: Handling Label Style Bias for Uncertain Image Segmentation
Kilian Zepf, Eike Petersen, Jes Frellsen +1
Segmentation uncertainty models predict a distribution over plausible segmentations for a given input, which they learn from the annotator variation in the training set. However, i…
Learning to Generate 3D Representations of Building Roofs Using Single-View Aerial Imagery
Maxim Khomiakov, Alejandro Valverde Mahou, Alba Reinders Sánchez +2
We present a novel pipeline for learning the conditional distribution of a building roof mesh given pixels from an aerial image, under the assumption that roof geometry follows a s…
Laplacian Segmentation Networks Improve Epistemic Uncertainty Quantification
Kilian Zepf, Selma Wanna, Marco Miani +5
Image segmentation relies heavily on neural networks which are known to be overconfident, especially when making predictions on out-of-distribution (OOD) images. This is a common s…
SolarDK: A high-resolution urban solar panel image classification and localization dataset
Maxim Khomiakov, Julius Holbech Radzikowski, Carl Anton Schmidt +4
The body of research on classification of solar panel arrays from aerial imagery is increasing, yet there are still not many public benchmark datasets. This paper introduces two no…