Research: Automated Asset Recognition using Machine Learning from Photogrammetry and LiDAR data
Funding: Bentley Systems
David is a Ph.D candidate currently working on image and point cloud segmentation/classification using machine learning techniques. This includes of photogrammetrically derived data from Unmanned Aerial Vehicles (UAVs), as well active sensors such as Terrestrial Laser Scanners (TLSs) and Mobile Mapping Systems. The research looks at the potential of deep learning (and in particular convolutional neural networks) for understanding these data sets.
David’s main academic interests include; computer vision and photogrammetry, and in particular the application of combining the two disiplines. Before beginning his PhD he completed a MSc at UCL in Remote Sensing/Environmental Mapping.