2 citations · 3 across the 4 of their papers we have counts for
4 papers
BugNIST -- a Large Volumetric Dataset for Object Detection under Domain Shift
Patrick Møller Jensen, Vedrana Andersen Dahl, Carsten Gundlach +3
Domain shift significantly influences the performance of deep learning algorithms, particularly for object detection within volumetric 3D images. Annotated training data is essenti…
Deep Active Latent Surfaces for Medical Geometries
Patrick M. Jensen, Udaranga Wickramasinghe, Anders B. Dahl +2
Shape priors have long been known to be effective when reconstructing 3D shapes from noisy or incomplete data. When using a deep-learning based shape representation, this often inv…
Review of Serial and Parallel Min-Cut/Max-Flow Algorithms for Computer Vision
Patrick M. Jensen, Niels Jeppesen, Anders B. Dahl +1
Minimum cut/maximum flow (min-cut/max-flow) algorithms solve a variety of problems in computer vision and thus significant effort has been put into developing fast min-cut/max-flow…
Weakly Supervised Volumetric Image Segmentation with Deformed Templates
Udaranga Wickramasinghe, Patrick M. Jensen, Mian Shah +2
There are many approaches to weakly-supervised training of networks to segment 2D images. By contrast, existing approaches to segmenting volumetric images rely on full-supervision…