2 citations · 2 across the 3 of their papers we have counts for
3 papers
OpenTrench3D: A Photogrammetric 3D Point Cloud Dataset for Semantic Segmentation of Underground Utilities
Lasse H. Hansen, Simon B. Jensen, Mark P. Philipsen +3
Identifying and classifying underground utilities is an important task for efficient and effective urban planning and infrastructure maintenance. We present OpenTrench3D, a novel a…
Prediction Confidence from Neighbors
Mark Philip Philipsen, Thomas Baltzer Moeslund
The inability of Machine Learning (ML) models to successfully extrapolate correct predictions from out-of-distribution (OoD) samples is a major hindrance to the application of ML i…
Distance in Latent Space as Novelty Measure
Mark Philip Philipsen, Thomas Baltzer Moeslund
Deep Learning performs well when training data densely covers the experience space. For complex problems this makes data collection prohibitively expensive. We propose to intellige…