7 citations · 12 across the 4 of their papers we have counts for
4 papers
Automated Linear Disturbance Mapping via Semantic Segmentation of Sentinel-2 Imagery
Andrew M. Nagel, Anne Webster, Christopher Henry +5
In Canada's northern regions, linear disturbances such as roads, seismic exploration lines, and pipelines pose a significant threat to the boreal woodland caribou population (Rangi…
Semantically-consistent Landsat 8 image to Sentinel-2 image translation for alpine areas
M. Sokolov, J. L. Storie, C. J. Henry +5
The availability of frequent and cost-free satellite images is in growing demand in the research world. Such satellite constellations as Landsat 8 and Sentinel-2 provide a massive…
Exploration of Convolutional Neural Network Architectures for Large Region Map Automation
R. M. Tsenov, C. J. Henry, J. L. Storie +3
Deep learning semantic segmentation algorithms have provided improved frameworks for the automated production of Land-Use and Land-Cover (LULC) maps, which significantly increases…
High-resolution semantically-consistent image-to-image translation
Mikhail Sokolov, Christopher Henry, Joni Storie +3
Deep learning has become one of remote sensing scientists' most efficient computer vision tools in recent years. However, the lack of training labels for the remote sensing dataset…