The rlr-tree: A reinforcement learning based r-tree for spatial data
Learned indexes have been proposed to replace classic index structures like B-Tree with
machine learning (ML) models. They require to replace both the indexes and query …
machine learning (ML) models. They require to replace both the indexes and query …
Machine learning meets big spatial data (revised)
The proliferation in amounts of generated data has propelled the rise of scalable machine
learning solutions to efficiently analyze and extract useful insights from such data …
learning solutions to efficiently analyze and extract useful insights from such data …
APRIL: Approximating Polygons as Raster Interval Lists
The spatial intersection join an important spatial query operation, due to its popularity and
high complexity. The spatial join pipeline takes as input two collections of spatial objects (eg …
high complexity. The spatial join pipeline takes as input two collections of spatial objects (eg …
[HTML][HTML] 3dpro: querying complex three-dimensional data with progressive compression and refinement
Large-scale three-dimensional spatial data has gained increasing attention with the
development of self-driving, mineral exploration, CAD, and human atlases. Such 3D objects …
development of self-driving, mineral exploration, CAD, and human atlases. Such 3D objects …