NR Researchers Arnt-Børre Salberg and Øivind Due Trier are now using deep learning for semi-automatic detection of charcoal kilns from airborne laser scanning (ALS) data. Preliminary results indicate that this is very effective compared to traditional pattern recognition methods.

With deep learning, 85% of the kilns are detected, with only 10% false positives in addition. With traditional pattern recognition on similar problems, the correct classification rate was lower, and the number of false positives was orders of magnitude higher.

A previously unknown grave field containing 16 grave mounds has recently been discovered by automatic pattern recognition software developed by the Norwegian Computing Center. Covered by spruce forest, the grave field is impossible to discover from aerial photography.

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In 2009, the project acquired two new Quickbird images of parts of Vestfold County. In one of the images, CultSearcher was able to detect nine circular crop marks that the archaeologists labeled as valid detections. Of these,

The Norwegian Computing Center has developed automatic detection of pits in airborne laser scanning data. This method is now being used in the mapping of ancient iron extraction sites and hunting systems in Oppland County, Norway.