Satellite
- Self-Supervised Lidar Place Recognition in Overhead Imagery Using Unpaired Data
- Point-based Metric and Topological Localisation between Lidar and Overhead Imagery
- RaVÆn: unsupervised change detection of extreme events using ML on-board satellites
- Unsupervised Change Detection of Extreme Events Using ML On-Board
- Self-supervised learning for using overhead imagery as maps in outdoor range sensor localization
- Get to the Point: Learning Lidar Place Recognition and Metric Localisation Using Overhead Imagery
- RainBench: Towards Data-Driven Global Precipitation Forecasting from Satellite Imagery
- Smart satellites: machine learning on-board for low-latency novelty detection
- Self-Supervised Localisation between Range Sensors and Overhead Imagery
- RSL-Net: Localising in Satellite Images From a Radar on the Ground
- Towards Data-Driven Physics-Informed Global Precipitation Forecasting from Satellite Imagery
- RainBench: Enabling Data-Driven Precipitation Forecasting on a Global Scale