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cs.CV2024
Impact of LiDAR visualisations on semantic segmentation of archaeological objects
Raveerat Jaturapitpornchai, Giulio Poggi, Gregory Sech +3
Deep learning methods in LiDAR-based archaeological research often leverage visualisation techniques derived from Digital Elevation Models to enhance characteristics of archaeologi…
cs.CV2024
Pansharpening of PRISMA products for archaeological prospection
Gregory Sech, Giulio Poggi, Marina Ljubenovic +2
Hyperspectral data recorded from satellite platforms are often ill-suited for geo-archaeological prospection due to low spatial resolution. The established potential of hyperspectr…
cs.CV2023
Transfer Learning of Semantic Segmentation Methods for Identifying Buried Archaeological Structures on LiDAR Data
Gregory Sech, Paolo Soleni, Wouter B. Verschoof-van der Vaart +3
When applying deep learning to remote sensing data in archaeological research, a notable obstacle is the limited availability of suitable datasets for training models. The applicat…