SCIPoC: Semantic Classification of Indoor Point Cloud: A study into the possibilities of classifying indoor point cloud using a Deep Learning approach

With the constantly evolving range of applications for technology the quality and amount of data constantly increases as well. In this growing data environment, there is a constant search to provide more value to all data that is available for as little effort as possible. Our research tries to add such additional value by diving into the...

Utilizing a Discrete Global Grid System For Handling Point Clouds With Varying Locations, Times, and Levels of Detail

Discrete Global Grid Systems (DGGS) have emerged in recent years as a new specification for working with global heterogeneous datasets of different types, such as vector, raster, and quantitative datasets. There exists no research on using point clouds with a DGGS. This research aims to analyse the extent to which a DGGS can be used to handle...