| scholarly article | Q13442814 |
| P356 | DOI | 10.1002/ARP.1806 |
| P953 | full work available at URL | http://dx.doi.org/10.1002/arp.1806 |
| https://onlinelibrary.wiley.com/doi/pdf/10.1002/arp.1806 |
| P2093 | author name string | Anna Schneider | |
| Thomas Raab | |||
| Alexandra Raab | |||
| Michael Breuß | |||
| Alexander Bonhage | |||
| Mahmoud Eltaher | |||
| P2860 | cites work | Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks | Q50628729 |
| Spatial distribution of relict charcoal hearths in the former royal forest district Tauer (SE Brandenburg, Germany) | Q55761268 | ||
| Pre-industrial charcoal production in Lower Lusatia (Brandenburg, Germany): Detection and evaluation of a large charcoal-burning field by combining archaeological studies, GIS-based analyses of shaded-relief maps and dendrochronological age determina | Q55761298 | ||
| Scale-space and edge detection using anisotropic diffusion | Q55967368 | ||
| Recent Trends and Long-standing Problems in Archaeological Remote Sensing | Q56476474 | ||
| Interpreting cultural remains in airborne laser scanning generated digital terrain models: effects of size and shape on detection success rates | Q60496585 | ||
| Selective woodland exploitation for charcoal production. A detailed analysis of charcoal kiln remains (ca. 1300–1900 AD) from Zoersel (northern Belgium) | Q60722000 | ||
| From features to fingerprints: A general diagnostic framework for anthropogenic geomorphology | Q63613270 | ||
| Reduced above-ground growth and wood density but increased wood chemical concentrations of Scots pine on relict charcoal hearths | Q89730247 | ||
| Identifying Landscape Modification using Open Data and Tools: The Charcoal Hearths of the Blue Mountain, Pennsylvania | Q100983291 | ||
| Defining what we study: The contribution of machine automation in archaeological research | Q106582533 | ||
| LiDAR-derived Local Relief Models - a new tool for archaeological prospection | Q106784779 | ||
| Detecting Neolithic Burial Mounds from LiDAR-Derived Elevation Data Using a Multi-Scale Approach and Machine Learning Techniques | Q106784811 | ||
| Combining Deep Learning and Location-Based Ranking for Large-Scale Archaeological Prospection of LiDAR Data from The Netherlands | Q106784836 | ||
| Past human impact in a mountain forest: geoarchaeology of a medieval glass production and charcoal hearth site in the Erzgebirge, Germany | Q108123756 | ||
| 2500 years of charcoal production in the Low Countries: The chronology and typology of charcoal kilns and their relation with early iron production | Q114137618 | ||
| High concentration of charcoal hearth remains as legacy of historical ferrous metallurgy in southern Poland | Q114149346 | ||
| Automated mound detection using lidar and object-based image analysis in Beaufort County, South Carolina | Q114627006 | ||
| Learning to Look at LiDAR: The Use of R-CNN in the Automated Detection of Archaeological Objects in LiDAR Data from the Netherlands | Q114871841 | ||
| Making LiGHT Work of Large Area Survey? Developing Approaches to Rapid Archaeological Mapping and the Creation of Systematic National-scaled Heritage Data | Q114871903 | ||
| The soil moisture regime of charcoal-enriched land use legacy sites | Q115446542 | ||
| Long term anthropogenic enrichment of soil organic matter stocks in forest soils – Detecting a legacy of historical charcoal production | Q115447334 | ||
| A Template-matching Approach Combining Morphometric Variables for Automated Mapping of Charcoal Kiln Sites | Q119411896 | ||
| Using deep neural networks on airborne laser scanning data: Results from a case study of semi‐automatic mapping of archaeological topography on Arran, Scotland | Q119412784 | ||
| Object‐based image analysis: a review of developments and future directions of automated feature detection in landscape archaeology | Q119412813 | ||
| P275 | copyright license | Creative Commons Attribution 4.0 International | Q20007257 |
| P6216 | copyright status | copyrighted | Q50423863 |
| P433 | issue | 2 | |
| P921 | main subject | archaeology | Q23498 |
| lidar | Q504027 | ||
| P304 | page(s) | 177-186 | |
| P577 | publication date | 2021-02-02 | |
| P1433 | published in | Archaeological Prospection | Q15760478 |
| P1476 | title | A modified Mask region‐based convolutional neural network approach for the automated detection of archaeological sites on high‐resolution light detection and ranging‐derived digital elevation models in the North German Lowland | |
| P478 | volume | 28 |
| Q119415188 | Applying automated object detection in archaeological practice: A case study from the southern Netherlands |
| Q119416774 | Automated large‐scale mapping and analysis of relict charcoal hearths in Connecticut (USA) using a Deep Learning YOLOv4 framework |
| Q119416386 | Investigating ancient agricultural field systems in Sweden from airborne LIDAR data by using convolutional neural network |
| Q125475030 | Lidar visualization techniques for the construction of geoarchaeological deposit models: An overview and evaluation in alluvial environments |
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