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Post-Disaster Building Database Updating Using Automated Deep Learning: An Integration of Pre-Disaster OpenStreetMap and Multi-Temporal Satellite Data

Saman Ghaffarian, Norman Kerle, Edoardo Pasolli, Jamal Jokar Arsanjani
2019 Remote Sensing  
In the present study, we use pre-disaster OpenStreetMap building data to automatically generate training samples to train the proposed deep learning approach after the co-registration of the map and the  ...  Deep learning and, in particular, convolutional neural network (CNN)-based approaches have recently become state-of-the-art methods to extract information from remote sensing images, in particular for  ...  Acknowledgments: The satellite images were provided by Digital Globe Foundation, which were granted for an ongoing project at ITC, University of Twente entitled "post-disaster recovery assessment using  ... 
doi:10.3390/rs11202427 fatcat:gbobccu6x5ecdaftren6v3yagm

Health Assessment of Eucalyptus Trees Using Siamese Network from Google Street and Ground Truth Images

Asim Khan, Warda Asim, Anwaar Ulhaq, Bilal Ghazi, Randall W. Robinson
2021 Remote Sensing  
Overall, this study shows that even in a complex background, most healthy and unhealthy Eucalyptus trees can be detected by our deep learning algorithm in real time.  ...  This paper proposes a deep learning-based network, Siamese convolutional neural network (SCNN), combined with a modified brute-force-based line-of-bearing (LOB) algorithm that evaluates the health of Eucalyptus  ...  [23] , face detection [24] , object detection [25] , using various deep learning algorithms [26] .  ... 
doi:10.3390/rs13112194 fatcat:w5ylbpb3kjcqhpmyzj7qekgwiy

Application Challenges from a Bird's-Eye View [chapter]

Davide Scaramuzza
2017 Computer Vision in Vehicle Technology  
It also serves as a reference for researchers of current developments and challenges in areas of the application of computer vision, involving vehicles such as advanced driver assistance (pedestrian detection  ...  classification and mapping, fire risk assessment).  ...  , and Ultraspectral Imagery.  ... 
doi:10.1002/9781118868065.ch6 fatcat:fsljmro5izhh5mp4z3hcrgstby

Unmanned Aerial Vehicles (UAVs): A Survey on Civil Applications and Key Research Challenges

Hazim Shakhatreh, Ahmad H. Sawalmeh, Ala Al-Fuqaha, Zuochao Dou, Eyad Almaita, Issa Khalil, Noor Shamsiah Othman, Abdallah Khreishah, Mohsen Guizani
2019 IEEE Access  
In this survey, we present UAV civil applications and their challenges. We also discuss current research trends and provide future insights for potential UAV uses.  ...  The use of unmanned aerial vehicles (UAVs) is growing rapidly across many civil application domains including real-time monitoring, providing wireless coverage, remote sensing, search and rescue, delivery  ...  UAV inspection program at AT&T uses deep learning algorithms on HD videos to detect defects and anomalies in real time [98] .  ... 
doi:10.1109/access.2019.2909530 fatcat:xgknpyuqazhpvferjkkdohxmtu

Computer Vision for Autonomous Vehicles: Problems, Datasets and State of the Art [article]

Joel Janai, Fatma Güney, Aseem Behl, Andreas Geiger
2021 arXiv   pre-print
Recent years have witnessed enormous progress in AI-related fields such as computer vision, machine learning, and autonomous vehicles.  ...  end-to-end learning for autonomous driving.  ...  They list ground, aerial, and satellite imagery, as well as Light Detection and Ranging (LiDAR) scans as the most commonly used sensor modality for urban reconstruction.  ... 
arXiv:1704.05519v3 fatcat:xiintiarqjbfldheeg2hsydyra

Outdoor Mobile Mapping and AI-Based 3D Object Detection with Low-Cost RGB-D Cameras: The Use Case of On-Street Parking Statistics

Stephan Nebiker, Jonas Meyer, Stefan Blaser, Manuela Ammann, Severin Rhyner
2021 Remote Sensing  
Our method combines georeferenced red-green-blue-depth (RGB-D) imagery from two low-cost 3D cameras with state-of-the-art 3D object detection algorithms for extracting and mapping parked vehicles.  ...  In an evaluation of suitable algorithms for detecting vehicles in the noisy and often incomplete 3D point clouds from RGB-D cameras, the 3D object detection network PointRCNN, which extends region-based  ...  and Arts Northwestern Switzerland for making this project possible and for their numerous and important inputs from the perspective of mobility experts.  ... 
doi:10.3390/rs13163099 fatcat:kzkofqzwxvbzlhlof5suognjoa

Geocoding of trees from street addresses and street-level images [article]

Daniel Laumer, Nico Lang, Natalie van Doorn, Oisin Mac Aodha, Pietro Perona, Jan Dirk Wegner
2020 arXiv   pre-print
To solve this assignment problem, we (i) detect trees in Google street-view panoramas using deep learning, (ii) combine multi-view detections per tree into a single representation, (iii) and match detected  ...  We introduce an approach for updating older tree inventories with geographic coordinates using street-level panorama images and a global optimization framework for tree instance matching.  ...  and Bruzzone, 2015) , only aerial imagery (Yang et al., 2009) , high-resolution satellite imagery (Li et al., 2016) , or medium resolution satellite imagery where tree identification and counting is  ... 
arXiv:2002.01708v1 fatcat:2yktxtxqjfc7bkx2ecjiauspva

Final Program

2020 2020 International Conference on Unmanned Aircraft Systems (ICUAS)  
Surface-Condition Detection System of Drone-Landing Space Using Ultrasonic Waves and Deep Learning, pp.  ...  Surface-Condition Detection System of Drone-Landing Space Using Ultrasonic Waves and Deep The large diversity of vegetation, terrain and railway settings increases the challenges for object detection and  ...  In a simulation experiment using deep learning, our system was able to determine whether a condition was suitable for landing with an accuracy of 98%.  ... 
doi:10.1109/icuas48674.2020.9214039 fatcat:7jr6chhfija47kgtwoxqmfmmoe

Radiation search operations using scene understanding with autonomous UAV and UGV

Gordon Christie, Adam Shoemaker, Kevin Kochersberger, Pratap Tokekar, Lance McLean, Alexander Leonessa
2017 Journal of Field Robotics  
The aerial data is used to identify radiological points of interest, generate an orthophoto along with a digital elevation model (DEM) of the scene, and perform semantic segmentation to assign a category  ...  In this paper, we present systems, algorithms, and experiments to perform radiation search using unmanned aerial vehicles (UAV) and unmanned ground vehicles (UGV) by employing semantic scene segmentation  ...  ., 2006 ], a self-supervised online learning algorithm is used on a UGV to learn a model that integrates information about the current terrain and overhead imagery that is then used to predict traversal  ... 
doi:10.1002/rob.21723 fatcat:dsloh5v4czb75lu3gjplcla34y

Image Based Mango Fruit Detection, Localisation and Yield Estimation Using Multiple View Geometry

Madeleine Stein, Suchet Bargoti, James Underwood
2016 Sensors  
To meet these challenges, we use a state-of-the-art CNN approach for fruit detection in individual monocular images, which can handle the variability in scale and illumination of the fruit.  ...  ) [21] ; stereo vision has been used to detect and associate apples [4, 22] .  ...  The small size of the cropped images also enabled learning deep CNN on a GPU, given their memory constraints. Individual fruits were annotated using rectangles, specifying their location and size.  ... 
doi:10.3390/s16111915 pmid:27854271 pmcid:PMC5134574 fatcat:dhgu2wexanhadfflgmdnvtvsuu

1986-1999 combined index IEEE aerospace and electronic systems magazine vols. 1-14 [Subject Index]

2000 IEEE Transactions on Aerospace and Electronic Systems  
AES-MApr93 57-61 spacecraft, satellites, and rockets; search strategy and 44 non-US abstracts.  ...  AES-M Jul88 papers from non-US joumals; 30 abstracts on space vehicles and satellite papers from non-US joumals; 38 abstracts on fiber optics.  ...  C., ZII, AES-MOct smart system for detecting and tracking targets in video imagery. Horton, surveillance appl. using multiple views of scene.  ... 
doi:10.1109/taes.2000.869530 fatcat:dqlflsnslveyri76fpijskbzqi