6 citations · 9 across the 8 of their papers we have counts for
9 papers
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 (…
From Expansion to Consolidation: Socio-Spatial Contagion Dynamics in Off-Grid PV Adoption
Roni Blushtein-Livnon, Tal Svoray, Itay Fischhendler +2
In traditional rural societies, where social ties are embedded in physical space, the diffusion of emerging technologies may be amplified through socio-spatial contagion (SSC). Suc…
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…
Beyond Leaders and Laggards: A Typology of Renewable Energy Adoption Trajectories with Evidence from Off-Grid Communities
Roni Blushtein-Livnon, Tal Svoray, Itay Ficshhendler +3
Understanding the dynamics of renewable energy adoption is essential for designing strategies that accelerate its spread - an urgent priority for advancing climate goals and improv…
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…
Prompt-Based Segmentation at Multiple Resolutions and Lighting Conditions using Segment Anything Model 2
Osher Rafaeli, Tal Svoray, Roni Blushtein-Livnon +1
This paper provides insights on the effectiveness of the zero shot, prompt-based Segment Anything Model (SAM) and its updated versions, SAM 2 and SAM 2.1, along with the non-prompt…