Taddeo D’Adamo, Simon Thivet, Catherine Pothier, Riccardo Simionato, Allan Fries, Jonathan Lemus, Costanza Bonadonna, Laure Tougne, Bertrand Kerautret · 2026 · Lecture notes in computer science
DOI: 10.1007/978-3-032-39385-2_26 · cited by 0 works (OpenAlex) · open-access PDF
تعتمد التحليل الكمي للظواهر البيئية بشكل متزايد على قياسات مبتكرة. في الفولاذيوسولوجيا، لا تزال تميزات الجغرافيا من الألواح والغابات الفولاذية من صور RGB محددة من قبل نقص حلول التجزئة المخصصة، وتبقى التوصيات المرتبطة بأجزاء من اليد العاملة على نطاق واسع. نحن نقدم GuidedSAM-Plume، إطار مفتوح مصمم من قبل الخبراء المصممة لتقسيمات تفاعلية من الألواح والغابات الفولاذية.
Machine translation (Meta M2M100); the English original follows.
Quantitative analysis of environmental phenomena increasingly relies on image-based measurements. In volcanology, the geometric characterization of volcanic plumes and clouds from RGB images remains hindered by the scarcity of dedicated segmentation solutions and partially handcrafted annotations remain widely prevalent. We present GuidedSAM-Plume, an open-source expert-guided framework tailored for the interactive segmentation of volcanic plumes and clouds. It leverages the zero-shot, spatial prompt-based capabilities of SAM2. The framework was thoroughly validated on a challenging dataset th
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Topics: Geology, Volcano, Segmentation, Remote sensing, Feature (linguistics), Noise (video)
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