3 citations · 11 across the 6 of their papers we have counts for
6 papers
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…
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…
Super-resolution of THz time-domain images based on low-rank representation
Marina Ljubenovic, Alessia Artesani, Stefano Bonetti +1
Terahertz time-domain spectroscopy (THz-TDS) employs sub-picosecond pulses to probe dielectric properties of materials giving as a result a 3-dimensional hyperspectral data cube. T…
Implicit neural representation for change detection
Peter Naylor, Diego Di Carlo, Arianna Traviglia +2
Identifying changes in a pair of 3D aerial LiDAR point clouds, obtained during two distinct time periods over the same geographic region presents a significant challenge due to the…
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…
Beam-Shape Effects and Noise Removal from THz Time-Domain Images in Reflection Geometry in the 0.25-6 THz Range
Marina Ljubenovic, Alessia Artesani, Stefano Bonetti +1
The increasing need of restoring high-resolution Hyper-Spectral (HS) images is determining a growing reliance on Computer Vision-based processing to enhance the clarity of the imag…