This article presents results of a case study within a project that seeks to develop heavily
automated analysis of digital topographic data to extract archaeological information and to …

The existing cultural heritage mapping in Norway is incomplete. Some selected areas are
mapped well, while the majority of areas only contain chance discoveries, often with bad …

Historical maps present a unique depiction of past landscapes, providing evidence for a
wide range of information such as settlement distribution, past land use, natural resources …

Until recently, archeological prospection using LiDAR data was based mainly on
expertbased and time-consuming visual analyses. Currently, deep learning convolutional …

Due to complicated backgrounds and unclear target orientation, automated object detection
is difficult in the field of archaeology. Most of the current convolutional neural network (CNN) …

Although the history of automated archaeological object detection in remotely sensed data is
short, progress and emerging trends are evident. Among them, the shift from rule-based …

This article presents a novel deep learning method for semi-automated detection of historic
mining pits using aerial LiDAR data. The recent emergence of national scale remotely …

This paper presents WODAN2. 0, a workflow using Deep Learning for the automated
detection of multiple archaeological object classes in LiDAR data from the Netherlands …

Computer-aided methods for the automatic detection of archaeological objects are needed
to cope with the ever-growing set of largely digital and easily available remotely sensed …

Rock art carvings, which are best described as petroglyphs, were produced by removing
parts of the rock surface to create a negative relief. This tradition was particularly strong …