Papers Building Damage Assessment
“Building Damage Assessment” 태그가 달린 논문 45편 · 필터 해제
Quantum-Grassmann-Plucker Token Mixing for Deep Learning-Based Post-Disaster Damage Assessment
Timely post-disaster building damage assessment from satellite imagery is a critical engineering decision support task, yet it remains constrained by class imbalance, ambiguous intermediate damage states, and limited cro…
Building Damage AssessmentQuantum Machine LearningImage ClassificationGeBDA: Building Damage Assessment as Text-Based Sequence Prediction
Conventionally, Building Damage Assessment (BDA) is tackled either with dedicated network architectures or by fine-tuning geospatial image foundation models. In this work, we ask whether a general-purpose Vision-Language…
Building Damage AssessmentDamage-TriageFormer: A Foundation-Model Framework for Typology-Based Building Damage Assessment from Mono-Temporal Imagery
Decision-relevant building damage assessment is critical for prioritizing resources and recovery after a disaster, yet most automated methods either flatten damage into a single severity scale (no damage, minor, major, d…
Building Damage AssessmentOptimizing Latent Representations for Robust Building Damage Assessment Onboard Earth Observation Satellites
Rapid identification of damaged buildings after natural disasters or on war areas is crucial to support emergency response and prioritize interventions. Earth Observation constellations provide timely, large-scale covera…
Building Damage AssessmentData AugmentationFrom Pixels to Semantics: A Multi-Stage AI Framework for Structural Damage Detection in Satellite Imagery
Rapid and accurate structural damage assessment following natural disasters is critical for effective emergency response and recovery. However, remote sensing imagery often suffers from low spatial resolution, contextual…
Building Damage AssessmentVideo RestorationObject DetectionDecision MakingTornadoNet: Real-Time Building Damage Detection with Ordinal Supervision
We present TornadoNet, a comprehensive benchmark for automated street-level building damage assessment evaluating how modern real-time object detection architectures and ordinal-aware supervision strategies perform under…
Building Damage AssessmentReal-Time Object DetectionOrdinal ClassificationImproved MambdaBDA Framework for Robust Building Damage Assessment Across Disaster Domains
Reliable post-disaster building damage assessment (BDA) from satellite imagery is hindered by severe class imbalance, background clutter, and domain shift across disaster types and geographies. In this work, we address t…
Building Damage AssessmentArchitectural Insights for Post-Tornado Damage Recognition
Rapid and accurate building damage assessment in the immediate aftermath of tornadoes is critical for coordinating life-saving search and rescue operations, optimizing emergency resource allocation, and accelerating comm…
Building Damage AssessmentBuilding Damage Detection using Satellite Images and Patch-Based Transformer Methods
Rapid building damage assessment is critical for post-disaster response. Damage classification models built on satellite imagery provide a scalable means of obtaining situational awareness. However, label noise and sever…
Building Damage AssessmentChessMamba: Structure-Aware Interleaving of State Spaces for Change Detection in Remote Sensing Images
Change detection (CD) in multitemporal remote sensing imagery presents significant challenges for fine-grained recognition, owing to heterogeneity and spatiotemporal misalignment. However, existing methodologies based on…
Building Damage AssessmentChange DetectionUniRSCD: A Unified Novel Architectural Paradigm for Remote Sensing Change Detection
In recent years, remote sensing change detection has garnered significant attention due to its critical role in resource monitoring and disaster assessment. Change detection tasks exist with different output granularitie…
Building Damage AssessmentChange DetectionThe Potential of Copernicus Satellites for Disaster Response: Retrieving Building Damage from Sentinel-1 and Sentinel-2
Natural disasters demand rapid damage assessment to guide humanitarian response. Here, we investigate whether medium-resolution Earth observation images from the Copernicus program can support building damage assessment,…
Building Damage AssessmentDeploying Rapid Damage Assessments from sUAS Imagery for Disaster Response
This paper presents the first AI/ML system for automating building damage assessment in uncrewed aerial systems (sUAS) imagery to be deployed operationally during federally declared disasters (Hurricanes Debby and Helene…
Building Damage AssessmentFlood-DamageSense: Multimodal Mamba with Multitask Learning for Building Flood Damage Assessment using SAR Remote Sensing Imagery
Most post-disaster damage classifiers succeed only when destructive forces leave clear spectral or structural signatures -- conditions rarely present after inundation. Consequently, existing models perform poorly at iden…
Building Damage AssessmentBuilding Flood Damage AssessmentFlooded Building SegmentationMambaNow you see it, Now you don't: Damage Label Agreement in Drone & Satellite Post-Disaster Imagery
This paper audits damage labels derived from coincident satellite and drone aerial imagery for 15,814 buildings across Hurricanes Ian, Michael, and Harvey, finding 29.02% label disagreement and significantly different di…
Building Damage AssessmentBuilding-Guided Pseudo-Label Learning for Cross-Modal Building Damage Mapping
Accurate building damage assessment using bi-temporal multi-modal remote sensing images is essential for effective disaster response and recovery planning. This study proposes a novel Building-Guided Pseudo-Label Learnin…
Building Damage AssessmentChange DetectionDisaster ResponsePseudo LabelDamageCAT: A Deep Learning Transformer Framework for Typology-Based Post-Disaster Building Damage Categorization
Natural disasters increasingly threaten communities worldwide, creating an urgent need for rapid, reliable building damage assessment to guide emergency response and recovery efforts. Current methods typically classify d…
Building Damage AssessmentDisaster ResponseChange3D: Revisiting Change Detection and Captioning from A Video Modeling Perspective
In this paper, we present Change3D, a framework that reconceptualizes the change detection and captioning tasks through video modeling. Recent methods have achieved remarkable success by regarding each pair of bi-tempora…
Building Damage AssessmentChange DetectionBRIGHT: A globally distributed multimodal building damage assessment dataset with very-high-resolution for all-weather disaster response
Disaster events occur around the world and cause significant damage to human life and property. Earth observation (EO) data enables rapid and comprehensive building damage assessment (BDA), an essential capability in the…
AllBuilding change detection for remote sensing imagesBuilding Damage AssessmentChange Detection+3Benchmarking Attention Mechanisms and Consistency Regularization Semi-Supervised Learning for Post-Flood Building Damage Assessment in Satellite Images
Post-flood building damage assessment is critical for rapid response and post-disaster reconstruction planning. Current research fails to consider the distinct requirements of disaster assessment (DA) from change detecti…
BenchmarkingBuilding Damage AssessmentChange Detection