Norman Kerle
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View article: Real-Time Bundle Adjustment for Ultra-High-Resolution UAV Imagery Using Adaptive Patch-Based Feature Tracking
Real-Time Bundle Adjustment for Ultra-High-Resolution UAV Imagery Using Adaptive Patch-Based Feature Tracking Open
Real-time processing of UAV imagery is crucial for applications requiring urgent geospatial information, such as disaster response, where rapid decision-making and accurate spatial data are essential. However, processing high-resolution im…
View article: Challenges and opportunities in the harmonization of trigger models for Anticipatory Action; a multi-hazard and multi-agency perspective
Challenges and opportunities in the harmonization of trigger models for Anticipatory Action; a multi-hazard and multi-agency perspective Open
Disaster risk financing has seen a transformative approach through Anticipatory Action (AA), designed to reduce shock and impact of multiple hazards on vulnerable population. The core of AA relies on pre-agreed triggering mechanisms, that …
View article: End-to-End Nano-Drone Obstacle Avoidance for Indoor Exploration
End-to-End Nano-Drone Obstacle Avoidance for Indoor Exploration Open
Autonomous navigation of drones using computer vision has achieved promising performance. Nano-sized drones based on edge computing platforms are lightweight, flexible, and cheap; thus, they are suitable for exploring narrow spaces. Howeve…
View article: Channel-Aware Distillation Transformer for Depth Estimation on Nano Drones
Channel-Aware Distillation Transformer for Depth Estimation on Nano Drones Open
Autonomous navigation of drones using computer vision has achieved promising performance. Nano-sized drones based on edge computing platforms are lightweight, flexible, and cheap, thus suitable for exploring narrow spaces. However, due to …
View article: Evaluating the explainability and performance of an elementary versus a statistical impact-based forecasting model
Evaluating the explainability and performance of an elementary versus a statistical impact-based forecasting model Open
The disaster risk community has notably shifted from a response-driven approach to making informed anticipatory action choices through impact-based forecasting (IBF). Algorithms are being developed and improved to increase impact predictio…
View article: Lite-Mono: A Lightweight CNN and Transformer Architecture for Self-Supervised Monocular Depth Estimation
Lite-Mono: A Lightweight CNN and Transformer Architecture for Self-Supervised Monocular Depth Estimation Open
Self-supervised monocular depth estimation that does not require ground truth for training has attracted attention in recent years. It is of high interest to design lightweight but effective models so that they can be deployed on edge devi…
View article: Microdrone-Based Indoor Mapping with Graph SLAM
Microdrone-Based Indoor Mapping with Graph SLAM Open
Unmanned aerial vehicles offer a safe and fast approach to the production of three-dimensional spatial data on the surrounding space. In this article, we present a low-cost SLAM-based drone for creating exploration maps of building interio…
View article: Towards Improved Unmanned Aerial Vehicle Edge Intelligence: A Road Infrastructure Monitoring Case Study
Towards Improved Unmanned Aerial Vehicle Edge Intelligence: A Road Infrastructure Monitoring Case Study Open
Consumer-grade Unmanned Aerial Vehicles (UAVs) are poorly suited to monitor complex scenes where multiple analysis tasks need to be carried out in real-time and in parallel to fulfil time-critical requirements. Therefore, we developed an i…
View article: Training a Disaster Victim Detection Network for UAV Search and Rescue Using Harmonious Composite Images
Training a Disaster Victim Detection Network for UAV Search and Rescue Using Harmonious Composite Images Open
Human detection in images using deep learning has been a popular research topic in recent years and has achieved remarkable performance. Training a human detection network is useful for first responders to search for trapped victims in deb…
View article: UNSUPERVISED HARMONIOUS IMAGE COMPOSITION FOR DISASTER VICTIM DETECTION
UNSUPERVISED HARMONIOUS IMAGE COMPOSITION FOR DISASTER VICTIM DETECTION Open
Deep detection networks trained with a large amount of annotated data achieve high accuracy in detecting various objects, such as pedestrians, cars, lanes, etc. These models have been deployed and used in many scenarios. A disaster victim …
View article: MICRO AND MACRO QUADCOPTER DRONES FOR INDOOR MAPPING TO SUPPORT DISASTER MANAGEMENT
MICRO AND MACRO QUADCOPTER DRONES FOR INDOOR MAPPING TO SUPPORT DISASTER MANAGEMENT Open
The use of drones to explore indoor spaces has gained attention and popularity for disaster management and indoor navigation applications. In this paper we present the operations and mapping techniques of two drones that are different in t…
View article: LISU: Low-light indoor scene understanding with joint learning of reflectance restoration
LISU: Low-light indoor scene understanding with joint learning of reflectance restoration Open
Semantic segmentation using convolutional neural networks (CNNs) achieves higher accuracy than traditional methods, but it fails to yield satisfactory results under illumination variants when the training set is limited. In this paper we p…
View article: TOWARDS LEARNING LOW-LIGHT INDOOR SEMANTIC SEGMENTATION WITH ILLUMINATION-INVARIANT FEATURES
TOWARDS LEARNING LOW-LIGHT INDOOR SEMANTIC SEGMENTATION WITH ILLUMINATION-INVARIANT FEATURES Open
Semantic segmentation models are often affected by illumination changes, and fail to predict correct labels. Although there has been a lot of research on indoor semantic segmentation, it has not been studied in low-light environments. In t…
View article: Agent-based modelling of post-disaster recovery with remote sensing data
Agent-based modelling of post-disaster recovery with remote sensing data Open
Disaster risk management, and post-disaster recovery (PDR) in particular, become increasingly important to assure resilient development. Yet, PDR is the most poorly understood phase of the disaster management cycle and can take years or ev…
View article: Review article: Towards resilient vital infrastructure systems – challenges, opportunities, and future research agenda
Review article: Towards resilient vital infrastructure systems – challenges, opportunities, and future research agenda Open
Infrastructure systems are inextricably tied to society by providing a variety of vital services. These systems play a fundamental role in reducing the vulnerability of communities and increasing their resilience to natural and human-induc…
View article: Integrating UAV and Ground Panoramic Images for Point Cloud Analysis of Damaged Building
Integrating UAV and Ground Panoramic Images for Point Cloud Analysis of Damaged Building Open
The effectiveness of damaged building investigation relies on rapid data collection, while jointly applying an unmanned aerial vehicle (UAV) and a backpack panoramic imaging system can quickly and comprehensively record the damage status. …
View article: Post-Disaster Building Damage Detection from Earth Observation Imagery Using Unsupervised and Transferable Anomaly Detecting Generative Adversarial Networks
Post-Disaster Building Damage Detection from Earth Observation Imagery Using Unsupervised and Transferable Anomaly Detecting Generative Adversarial Networks Open
We present an unsupervised deep learning approach for post-disaster building damage detection that can transfer to different typologies of damage or geographical locations. Previous advances in this direction were limited by insufficient q…
View article: INFRASTRUCTURE DEGRADATION AND POST-DISASTER DAMAGE DETECTION USING ANOMALY DETECTING GENERATIVE ADVERSARIAL NETWORKS
INFRASTRUCTURE DEGRADATION AND POST-DISASTER DAMAGE DETECTION USING ANOMALY DETECTING GENERATIVE ADVERSARIAL NETWORKS Open
Degradation and damage detection provides essential information to maintenance workers in routine monitoring and to first responders in post-disaster scenarios. Despite advance in Earth Observation (EO), image analysis and deep learning te…
View article: Post-Disaster Recovery Monitoring with Google Earth Engine
Post-Disaster Recovery Monitoring with Google Earth Engine Open
Post-disaster recovery is a complex process in terms of measuring its progress after a disaster and understanding its components and influencing factors. During this process, disaster planners and governments need reliable information to m…
View article: Detection of seismic façade damages with multi-temporal oblique aerial imagery
Detection of seismic façade damages with multi-temporal oblique aerial imagery Open
Remote sensing images have long been recognized as useful for the detection of building damages, mainly due to their wide coverage, revisit capabilities and high spatial resolution. The majority of contributions aimed at identifying debris…
View article: Towards Resilient Vital Infrastructure Systems: Challenges, Opportunities, and Future Research Agenda
Towards Resilient Vital Infrastructure Systems: Challenges, Opportunities, and Future Research Agenda Open
Infrastructure systems are inextricably tied to society by providing a variety of vital services. These systems play a fundamental role in reducing the vulnerability of communities and increasing their resilience to natural and human-induc…
View article: novelty and significance unclear
novelty and significance unclear Open
Review of nhess-2019-219, High-frequency glacial lake mapping using time series of Sentinel-1A/1B SAR imagery: An assessment for southeastern Tibetan PlateauThe purpose of the paper is to develop a methodology to map the extent of glacial …
View article: The Influence of Surface Topography on the Weak Ground Shaking in Kathmandu Valley during the 2015 Gorkha Earthquake, Nepal
The Influence of Surface Topography on the Weak Ground Shaking in Kathmandu Valley during the 2015 Gorkha Earthquake, Nepal Open
It remains elusive why there was only weak and limited ground shaking in Kathmandu valley during the 25 April 2015 Mw 7.8 Gorkha, Nepal, earthquake. Our spectral element numerical simulations show that, during this earthquake, surface topo…
View article: Accuracy assessment of real-time kinematics (RTK) measurements on unmanned aerial vehicles (UAV) for direct geo-referencing
Accuracy assessment of real-time kinematics (RTK) measurements on unmanned aerial vehicles (UAV) for direct geo-referencing Open
Geospatial information acquired with Unmanned Aerial Vehicles (UAV) provides valuable decision-making support in many different domains, and technological advances coincide with a demand for ever more sophisticated data products. One conse…
View article: A Proof-of-Concept of Integrating Machine Learning, Remote Sensing, and Survey Data in Evaluations. The Measurement of Disaster Resilience in the Philippines
A Proof-of-Concept of Integrating Machine Learning, Remote Sensing, and Survey Data in Evaluations. The Measurement of Disaster Resilience in the Philippines Open
Disaster resilience is a topic of increasing importance for policy makers in the context of climate change. However, measuring disaster resilience remains a challenge as it requires information on both the physical environment and socio-ec…
View article: UAV-Based Structural Damage Mapping: A Review
UAV-Based Structural Damage Mapping: A Review Open
Structural disaster damage detection and characterization is one of the oldest remote sensing challenges, and the utility of virtually every type of active and passive sensor deployed on various air- and spaceborne platforms has been asses…