Part 3 of a series about the SpaceNet 4: Off-Nadir Dataset and Building Detection Challenge.
Archives for 2018
Part 2 of a discussion about an introductory outline for some of our work in exploring the relationships between super-resolution (SR) and object detection algorithms in satellite imagery.
Discussing the interplay between super-resolution techniques and object detection frameworks, which remains largely unexplored, particularly in the context of satellite or overhead imagery.
Lab41 discusses the security of data used in training a neural network.
Updating maps is currently a highly manual process requiring a large number of human labelers to either create features or rigorously validate automated outputs. We propose that the frequent revisits of earth imaging satellite constellations may accelerate existing efforts to quickly update foundational maps when combined with advanced machine learning techniques.