
At present, at most ports the code of each container is registered manually, which is of a great potential safety hazard and inefficient. In this paper we present a container-code recognition system, which use the geometrical clustering of connected component extracted by MSER descriptor and spatial structure template matching for location and various CNN-classifiers for identification. Experiments confirmed the robustness and accurateness of the recognition algorithm on real images from ports.
| 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). | 6 | |
| 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. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
