
Automatic extraction of roads from aerial photos has been demonstrated in a number of systems, but the systems which display the better capabilities usually rely on manual selection of road starting points. This interaction with a human operator is eliminated by integrating a road-finding module into a road network extraction system. The road finder combines a greedy, edge-based, road-center linker with a smoothness checking program and a post linking process. It is used both for determining where the tracking process is to begin, and for restarting when tracking fails. Results from the fully implemented system are presented. >
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 4 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
