Structural Damage

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4 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

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Embedded Bi-Temporal Building Damage Assessment for On-Board Data Reduction
Sep 29, 2026Thomas Goudemant, Benjamin Francesconi, Marjorie Bellizzi +1Post-Disaster Damage Assessment Structural Damage
IRT Saint Exupéry, France · CNES, France
Analog Computing revisited: A fully analog and minimalistic Damage Detector for Ultrasonic Testing enabling Material-Integrated Structural Health Monitoring
Sep 28, 2026Stefan BossePiezoelectric Transducers Robotic Ultrasound
University of Koblenz, Practical Computer Science, Koblenz, Germany
The Undetected Damage of Quantization on Retrieval and How to Fix It
Sep 21, 2026Luca Zhou, Alessandro Zirilli, Daniele Solombrino +2Quantized Full-Precision Performance
Sapienza University of Rome · Not Diamond · Paradigma
How Much is a Human Right Worth? ECtHR-NPD: A Benchmark for Predicting Non-Pecuniary Damage Awards
Sep 16, 2026Yanyi Pu, Damian A. Gonzalez-Salzberg, Zheng Yuan +1Legal Domain Legal Natural Language Processing Benchmarks
School of Computer Science, University of Sheffield · Birmingham Law School, University of Birmingham
Integrated Laser Scanning and Image-Based Topology Optimization Techniques for Detection and Quantification of Visible and Subsurface Structural Defects
Sep 1, 2026Mehrdad Shafiei Dizaji, Devin HarrisDefect Detection Subsurface Scattering
Department of Engineering Systems and Environment, University of Virginia, Charlottesville, VA, USA
RAPIDMap: Rapid Multi-Agent Pipeline for Interpretable Disaster Mapping from Satellite and Street-view Imagery
Aug 30, 2026Yifan Yang, Lei ZouPost-Disaster Damage Assessment Geospatial Reasoning
Department of Geography, Texas A&M University, College Station, TX, USA
Damage Classification for 3D Point Cloud Data via 3D Data Analysis and Vision Foundation Model-based 2D Projections
Aug 9, 2026Evan Perez, Kalelo Dukuray, Erika Ardiles-Cruz +1Point Clouds Interactive 3D Segmentation
Dept. of Computer Science, City College of New York, NY 10031, USA · Air Force Research Lab, Rome, NY 13441, USA
Integrated Multimodal AI System for Retrieval-Augmented Reasoning, Object Sensing, and Damage Analysis
Aug 9, 2026Kalelo Dukuray, Israel Pina, Evan Perez +2Multimodal Retrieval Augmented Generation Structural Damage
Dept. of Computer Science, City College of New York, New York, NY 10031, USA · Air Force Research Lab, Rome, NY 13441, USA
MOSAIK: Multi-Patch Content-Aware Spatial Allocation of Image Tokens for Efficient Generation
Aug 5, 2026Mohammadreza Hami, Mohammadreza Samadi, Chao Gao +1Visual Tokenizers Iterative Denoising Methods
Huawei Technologies Canada
Assessing the Benefits of Combining Advanced Deep Learning Techniques for Post-Disaster Building Damage Assessment from UAV Imagery
Aug 3, 2026Huy Quang Ung, Guillaume Habault, Roberto Legaspi +3Post-Disaster Damage Assessment Structural Damage
KDDI Research, Inc., Fujimino, Japan
The Cross-Domain Generalization Cost of Offensive Language Detection
Jul 26, 2026Ruixing Ren, Junhui Zhao, Xiaoke Sun +1Large Language Model Adaptation Multilingual
School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China · National Computer Network Emergency Response Technical Team/Coordination Center of China (CNCERT/CC), Beijing 100029, China
DART: A Degradation-Aware Recurrent Transformer for Archival Film Restoration
Jul 23, 2026Mikołaj Jastrzębski, Wojciech Kozłowski, Kamil AdamczewskiVideo Restoration Query-Specific Degradation-Aware Representation
Wrocław University of Science and Technology
CausalGate: Causal Importance Distillation for Transformer Module Pruning
Jul 21, 2026Kiran Nair, Smriti Regmi, Rodrigue RizkLLM Inference Optimization Transformer Architectures
USD Artificial Intelligence Research Lab, Department of Computer Science University of South Dakota, Vermillion, SD 57069, USA
Stress-Sharing: A Bio-Inspired Approach to Decentralized Fault Repair in Modular Spacecraft
Jul 15, 2026Sidhdharth D. Sikka, Yue Shen, Shaoshuai MouSelf-Repair Spacecraft
Purdue University, West Lafayette, IN, USA · Manifold Research Group
Erasing Without Collateral Damage: Precise Concept Removal in Diffusion Models
Jul 6, 2026Parth Upman, Nishita Jain, Shreyank N GowdaConcept Erasure Text-To-Image Diffusion Models
School of Computer Science, University of Nottingham, Nottingham, NG8 1BB, UK · Department of Computing, Imperial College London, London, SW7 2AZ, UK
Not All Prediction Targets Keep Training-Free Diffusion Guidance on the Manifold
Jul 1, 2026Yunsung Lee, Hyeongmin LeeClassifier-Free Guidance Diffusion Models
MAUM.AI, Republic of Korea · Seoul National University of Science and Technology, Republic of Korea
A Multi-Fidelity Convolutional Autoencoder-Transfer Learning Framework for Guided-Wave-Based Damage Diagnosis Using Large Simulated and Limited Experimental Datasets
Jun 25, 2026Santosh Kapuria, AbhishekWavelets Physics-Guided Machine Learning
Department of Applied Mechanics, Indian Institute of Technology Delhi, New Delhi, 110016, Delhi, India
Transformer-based Multisensor Data Fusion of Ultrasonic Guided Wave and FBG-based Strain Measurements for Multitask Aerospace Structural Health Monitoring
Jun 24, 2026Xin Yang, Morteza Moradi, Tongtong Yan +4Multi-Sensor Fusion Piezoelectric Transducers
Department of Mechanical Engineering & Division of Mechatronic System Dynamics (LMSD), KU Leuven, Belgium · Center of Excellence in Artificial Intelligence for Structures, Prognostics & Health Management, Aerospace Engineering Faculty, Delft University of Technology, Kluyverweg 1, Delft, 2629 HS, the Netherlands · Department of Civil Engineering, The University of British Columbia, Vancouver, Canada +2
Beyond Damage Assessment: Recyclable Material Detection in Aerial Disaster Imagery Using a Lightweight Patch-Based Framework
Jun 19, 2026Mahmoud Hazem, Karim HammoudiPost-Disaster Damage Assessment Aerial Imagery
Independent Researcher · Cairo, Egypt · Université de Haute-Alsace, IRIMAS +1
A Formal Resilience Framework for Cyber-Physical Embodied Systems under Device-Level Cyberattacks
Jun 15, 2026Alberto GiarettaCyber-Physical System Resilience
Department of Computer Science, Örebro University, Sweden · AI, Robotics and Cybersecurity Center (ARC), Örebro University, Sweden
Damage-TriageFormer: A Foundation-Model Framework for Typology-Based Building Damage Assessment from Mono-Temporal Imagery
Jun 10, 2026Yiming Xiao, Yu-Hsuan Ho, Sanjay Thasma +2Post-Disaster Damage Assessment Structural Damage
Texas A&M University · Resilitix Intelligence LLC · Institute for a Disaster Resilient Texas
Perplexity Can Miss SAE Feature Damage Under Quantization
Jun 2, 2026Evan DuanQuantizer Model Activations
University of Michigan
Fine-Tuning Vision-Language Models for Understanding Current Damage and Scoring Priority with Quality Guard Agent
May 24, 2026Takato YasunoRecent Vision-Language Models Structural Damage
WaveGraphNet: Physics-Consistent Guided-Wave Damage Localization through Coupled Inverse-Forward Graph Learning
May 19, 2026Vinay Sharma, Aditya Bharade, Olga FinkStructural Damage
EPFL, Intelligent Maintenance and Operations Systems, Lausanne, Switzerland
DA-SegFormer: Damage-Aware Semantic Segmentation for Fine-Grained Disaster Assessment
May 11, 2026Kevin Zhu, William Tang, Raphael Hay Tene +3Post-Disaster Damage Assessment Structural Damage
Bina Labs, Lehigh University
Minimizing Collateral Damage in Activation Steering
May 1, 2026Tam Nguyen, Tu Anh Nguyen, Sina Alemohammad +1Linear Activation Steering Model Activations
Department of Electrical & Computer Engineering, Rice University, Houston, USA · Department of Computational and Applied Mathematics, Rice University, Houston, USA · Department of Electrical & Computer Engineering, The University of Texas at Austin, Austin, USA
Disentangling Damage from Operational Variability: A Label-Free Self-Supervised Representation Learning Framework for Output-Only Structural Damage Identification
Apr 21, 2026Xudong Jian, Charikleia Stoura, Simon Scandella +1Vibration Structural Damage
Department of Civil, Environmental and Geomatic Engineering, ETH Zürich, Zürich, Switzerland. · Department of Mechanical Engineering, Politecnico di Milano, Italy
MS-SSE-Net: A Multi-Scale Spatial Squeeze-and-Excitation Network for Structural Damage Detection in Civil and Geotechnical Engineering
Apr 16, 2026Saif ur Rehman Khan, Imad Ahmed Waqar, Arooj Zaib +4Structural Damage Spatial Attention
Department of Computer Science, Rhineland-Palatinate Technical2026 University of Kaiserslautern-Landau, orgaddressKaiserslautern, 67663, Germany.Apr · 4BiogentX (biogentx.com, Renala Khurd, District Okara, Punjab, Pakistan. · 2German Research Center for Artificial Intelligence, Kaiserslautern, 67663, Germany. +2

Sep 29, 2026, cs.CVJ/K move · Enter open · S save

Embedded Bi-Temporal Building Damage Assessment for On-Board Data Reduction

Thomas Goudemant, Benjamin Francesconi, Marjorie Bellizzi, Adrien Dorise

IRT Saint Exupéry, France · CNES, France

Post-Disaster Damage Assessment Structural Damage Satellite Data

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Rapid assessment of building damage after natural disasters is essential to support emergency response. Earth Observation satellites can acquire relevant imagery shortly after an event, but exploitation is limited by uplink and downlink capacity and by ground-processing latency. We address this with a bi-temporal building damage assessment pipeline built on a siamese detector derived from YOLOX, designed to compress information at both ends of the ground/space link. On the ground, pre-disaster reference images are encoded into a compact latent space -- compressed by up to a factor of 64 -- and uplinked to the satellite. On board, this reference is compared with a fresh post-disaster acquisition so that the downlink carries only actionable object-level products, bounding boxes and damage classes, instead of full scenes. This cuts the data exchanged in both directions, while on xBD the strongly compressed reference still preserves most of the detection performance. Because on-board acquisitions suffer from residual pre/post co-registration errors, we introduce a latent-space shift estimation and correction module that regresses the global offset from the coarse feature level and realigns the post-disaster features before fusion. It substantially improves robustness to de-registration -- especially under large shifts, where fusion-only variants collapse -- while also raising nominal accuracy and remaining compatible with the strongest compression. We finally port the pipeline to two embedded targets, a Xilinx Versal VCK190 and an NVIDIA Jetson AGX Orin, and report hardware performance (latency, throughput, power efficiency). The core detector and its compression port cleanly to both, but the operators needed for long-range robustness survive only on the Jetson GPU, whereas the Versal DPU does not.

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