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Impact of LiDAR visualisations on semantic segmentation of archaeological objects
Deep learning methods in LiDAR-based archaeological research often leverage visualisation techniques derived from Digital Elevation Models to enhance characteristics of archaeological objects present in the images.
Pansharpening of PRISMA products for archaeological prospection
Hyperspectral data recorded from satellite platforms are often ill-suited for geo-archaeological prospection due to low spatial resolution.
Transfer Learning of Semantic Segmentation Methods for Identifying Buried Archaeological Structures on LiDAR Data
When applying deep learning to remote sensing data in archaeological research, a notable obstacle is the limited availability of suitable datasets for training models.
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