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Exploring Semi-Automatic Map Labeling
In an iterative human-in-the-loop process alternating between user modifications and local algorithmic updates and refinements the labeling can be tuned to the user's needs.
An Algorithmic Study of Fully Dynamic Independent Sets for Map Labeling
Map labeling is a classical problem in cartography and geographic information systems (GIS) that asks to place labels for area, line, and point features, with the goal to select and place the maximum number of independent, i. e., overlap-free, labels.
Computational Geometry Data Structures and Algorithms
Exploring Negatives in Contrastive Learning for Unpaired Image-to-Image Translation
Recently, contrastive learning (CL) has been used to further investigate the image correspondence in unpaired image translation by using patch-based positive/negative learning.
