Accurate and up-to-date maps of built-up areas are crucial to support sustainable urban
development. Earth Observation (EO) is a valuable data source to cover this demand. In …

Deep learning techniques have the potential to provide versatile solutions for automated
semantic segmentation of bridge point clouds, but previous studies were limited to small …

Paris-CARLA-3D is a dataset of several dense colored point clouds of outdoor environments
built by a mobile LiDAR and camera system. The data are composed of two sets with …

Borescope inspection is a labour-intensive process used to find defects in aircraft engines
that contain areas not visible during a general visual inspection. The outcome of the process …

Oil spillage over a sea or ocean surface is a threat to marine and coastal ecosystems.
Spaceborne synthetic aperture radar (SAR) data have been used efficiently for the detection …

The rising severity and frequency of wildfires in recent years in the United States have raised
numerous concerns regarding the improvement in wildfire emergency response …

Urbanization is progressing at an unprecedented rate in many places around the world. The
Sentinel-1 synthetic aperture radar (SAR) and Sentinel-2 MultiSpectral Instrument (MSI) …

In this study, a Semi-Supervised Learning (SSL) method for improved urban change
detection from bi-temporal image pairs is presented. The proposed method employs a Dual …

It is widely thought that considerable manual rework is a necessity in the production of
aerospace composite structures manufactured through automated fiber placement (AFP) …

We propose a unique dataset with star images, their centroids, and a new centroid algorithm
based on machine learning, that significantly improves star image centroid performance …