6 citations · 9 across the 6 of their papers we have counts for
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cs.CV2024★ 6 cited
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…
cs.CV2024★ 3 cited
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…