23 citations · 29 across the 5 of their papers we have counts for
5 papers
Magnifier: A Multi-grained Neural Network-based Architecture for Burned Area Delineation
Daniele Rege Cambrin, Luca Colomba, Paolo Garza
In crisis management and remote sensing, image segmentation plays a crucial role, enabling tasks like disaster response and emergency planning by analyzing visual data. Neural netw…
Turin3D: Evaluating Adaptation Strategies under Label Scarcity in Urban LiDAR Segmentation with Semi-Supervised Techniques
Luca Barco, Giacomo Blanco, Gaetano Chiriaco +6
3D semantic segmentation plays a critical role in urban modelling, enabling detailed understanding and mapping of city environments. In this paper, we introduce Turin3D: a new aeri…
ViGEO: an Assessment of Vision GNNs in Earth Observation
Luca Colomba, Paolo Garza
Satellite missions and Earth Observation (EO) systems represent fundamental assets for environmental monitoring and the timely identification of catastrophic events, long-term moni…
DQNC2S: DQN-based Cross-stream Crisis event Summarizer
Daniele Rege Cambrin, Luca Cagliero, Paolo Garza
Summarizing multiple disaster-relevant data streams simultaneously is particularly challenging as existing Retrieve&Re-ranking strategies suffer from the inherent redundancy of mul…
CaBuAr: California Burned Areas dataset for delineation
Daniele Rege Cambrin, Luca Colomba, Paolo Garza
Forest wildfires represent one of the catastrophic events that, over the last decades, caused huge environmental and humanitarian damages. In addition to a significant amount of ca…