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FMARS: Annotating Remote Sensing Images for Disaster Management using Foundation Models
Edoardo Arnaudo, Jacopo Lungo Vaschetti, Lorenzo Innocenti +4
Very-High Resolution (VHR) remote sensing imagery is increasingly accessible, but often lacks annotations for effective machine learning applications. Recent foundation models like…
Robust Burned Area Delineation through Multitask Learning
Edoardo Arnaudo, Luca Barco, Matteo Merlo +1
In recent years, wildfires have posed a significant challenge due to their increasing frequency and severity. For this reason, accurate delineation of burned areas is crucial for e…
A Contrastive Distillation Approach for Incremental Semantic Segmentation in Aerial Images
Edoardo Arnaudo, Fabio Cermelli, Antonio Tavera +2
Incremental learning represents a crucial task in aerial image processing, especially given the limited availability of large-scale annotated datasets. A major issue concerning cur…