Applying automated object detection in archaeological practice: A case study from the southern Netherlands
出版年份 2021 全文链接
标题
Applying automated object detection in archaeological practice: A case study from the southern Netherlands
作者
关键词
-
出版物
Archaeological Prospection
Volume -, Issue -, Pages -
出版商
Wiley
发表日期
2021-06-18
DOI
10.1002/arp.1833
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- 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
- (2021) Alexander Bonhage et al. Archaeological Prospection
- Deep Learning in Archaeological Remote Sensing: Automated Qanat Detection in the Kurdistan Region of Iraq
- (2020) Mehrnoush Soroush et al. Remote Sensing
- Machine Learning for Cultural Heritage: A Survey
- (2020) Marco Fiorucci et al. PATTERN RECOGNITION LETTERS
- Combining Deep Learning and Location-Based Ranking for Large-Scale Archaeological Prospection of LiDAR Data from The Netherlands
- (2020) Wouter B. Verschoof-van der Vaart et al. ISPRS International Journal of Geo-Information
- Learning to Classify Structures in ALS-Derived Visualizations of Ancient Maya Settlements with CNN
- (2020) Maja Somrak et al. Remote Sensing
- A Pilot Study on Remote Sensing and Citizen Science for Archaeological Prospection
- (2020) Christopher Stewart et al. Remote Sensing
- Automated mapping of cultural heritage in Norway from airborne lidar data using faster R-CNN
- (2020) Øivind Due Trier et al. International Journal of Applied Earth Observation and Geoinformation
- Integrating Remote Sensing, Machine Learning, and Citizen Science in Dutch Archaeological Prospection
- (2019) Karsten Lambers et al. Remote Sensing
- Bringing Lunar LiDAR Back Down to Earth: Mapping Our Industrial Heritage through Deep Transfer Learning
- (2019) Gallwey et al. Remote Sensing
- Convolutional neural networks for archaeological site detection – Finding “princely” tombs
- (2019) Gino Caspari et al. JOURNAL OF ARCHAEOLOGICAL SCIENCE
- Focal loss for dense object detection
- (2018) Tsung-Yi Lin et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Using deep neural networks on airborne laser scanning data: Results from a case study of semi-automatic mapping of archaeological topography on Arran, Scotland
- (2018) Øivind Due Trier et al. Archaeological Prospection
- Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
- (2017) Shaoqing Ren et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Geospatial Big Data and archaeology: Prospects and problems too great to ignore
- (2017) Mark D. McCoy JOURNAL OF ARCHAEOLOGICAL SCIENCE
- Detection of Fragmented Rectangular Enclosures in Very High Resolution Remote Sensing Images
- (2016) Igor Zingman et al. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
- Deep learning for visual understanding: A review
- (2016) Yanming Guo et al. NEUROCOMPUTING
- ImageNet Large Scale Visual Recognition Challenge
- (2015) Olga Russakovsky et al. INTERNATIONAL JOURNAL OF COMPUTER VISION
- Deep learning
- (2015) Yann LeCun et al. NATURE
- Interpreting cultural remains in airborne laser scanning generated digital terrain models: effects of size and shape on detection success rates
- (2013) Ole Risbøl et al. JOURNAL OF ARCHAEOLOGICAL SCIENCE
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