6 citations · 9 across the 8 of their papers we have counts for
7 papers · 1 filter
Evaluating Semantic and Spatial Guidance for Foundation Model Segmentation of Small-Scale PV in Remote Sensing Imagery
Roni Blushtein-Livnon, Tal Svoray, Osher Rafaeli +4
Spatio-temporal PV data are essential for understanding adoption processes in off-grid regions, yet such data remain largely unavailable. Automated segmentation of remote sensing (…
Test-Time Adaptation for Height Completion via Self-Supervised ViT Features and Monocular Foundation Models
Osher Rafaeli, Tal Svoray, Ariel Nahlieli
Accurate digital surface models (DSMs) are essential for many geospatial applications, including urban monitoring, environmental analyses, infrastructure management, and change det…
On the Effectiveness of Textual Prompting with Lightweight Fine-Tuning for SAM3 Remote Sensing Segmentation
Roni Blushtein-Livnon, Osher Rafaeli, David Ioffe +3
Remote sensing (RS) image segmentation is constrained by the limited availability of annotated data and a gap between overhead imagery and natural images used to train foundational…
Seamless High-Resolution Terrain Reconstruction: A Prior-Based Vision Transformer Approach
Osher Rafaeli, Tal Svoray, Ariel Nahlieli
High-resolution elevation data is essential for hydrological modeling, hazard assessment, and environmental monitoring; however, globally consistent, fine-scale Digital Elevation M…
SinkSAM-Net: Knowledge-Driven Self-Supervised Sinkhole Segmentation Using Topographic Priors and Segment Anything Model
Osher Rafaeli, Tal Svoray, Ariel Nahlieli
Soil sinkholes significantly influence soil degradation, infrastructure vulnerability, and landscape evolution. However, their irregular shapes, combined with interference from sha…
Performance of Human Annotators in Object Detection and Segmentation of Remotely Sensed Data
Roni Blushtein-Livnon, Tal Svoray, Michael Dorman
This study introduces a laboratory experiment designed to assess the influence of annotation strategies, levels of imbalanced data, and prior experience, on the performance of huma…