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Found 6 papers, 1 papers with code
ICDAR 2021 Competition on Historical Map Segmentation
Task~2 consists in segmenting map content from the larger map sheet, and was won by the UWB team using a U-Net-like FCN combined with a binarization method to increase detection edge accuracy.
Combining Deep Learning and Mathematical Morphology for Historical Map Segmentation
Our contribution is a pipeline that combines the strengths of CNN (efficient edge detection and filtering) and MM (guaranteed extraction of closed shapes) in order to achieve such a task.
A state of the art of urban reconstruction: street, street network, vegetation, urban feature
The main challenges seems to come from the complex nature of urban environment and from the limitations of the available data.
Interactive in-base street model edit: how common GIS software and a database can serve as a custom Graphical User Interface
Tools are needed to efficiently create and edit those vector geospatial data.
An octree cells occupancy geometric dimensionality descriptor for massive on-server point cloud visualisation and classification
In the last decade the use of Machine Learning and more specifically classification methods have proved to be successful to create this semantic information.
Implicit LOD using points ordering for processing and visualisation in Point Cloud Servers
Lidar datasets now commonly reach Billions of points and are very dense.
