Taddeo D'Adamo, Simon Thivet, Catherine Pothier, Riccardo Simionato, Allan Fries, Jonathan Lemus, Costanza Bonadonna, Laure Tougne Rodet · 2026 · arXiv
DOI: 10.48550/arXiv.2610.29825 · open-access PDF
Analisis kuantitatif dari fenomena lingkungan semakin bergantung pada pengukuran berbasis gambar. Dalam vulkanologi, karakterisasi geometris dari bulu vulkanik dan awan dari gambar RGB tetap terhalang oleh kekurangan solusi segmentasi khusus dan anotasi sebagian buatan tangan tetap prevalen. Kami menyajikan GuidedSAM-Plume, sebuah framework sumber terbuka yang dipandu oleh para ahli yang disesuaikan untuk segmentasi interaktif dari bulu vulkanik dan awan. Ini memanfaatkan kemampuan zero-shot, spatial prompt-based SAM2.
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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