Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 21 for “"LiDAR point clouds"”.
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Self-Supervised Learning Method for Semantic Segmentation of LiDAR Point Clouds
… advancements in semantic segmentation for LiDAR point clouds, largely the adopting of deep learning techniques. There are the related works of 3D semantic segmentation, including neural network models to process converted voxels, points, and graphs. However, point-based methods are not …
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Advanced Methods for Change Detection in LiDAR Data and Hyperspectral Images
… been developed. Light Detection And Ranging (LiDAR) and Hyperspectral (HS) sensors acquire data that accurately characterize the 3-D structure and the spectral signature of the area of interest, respectively. With the upcoming generation of small sensors designed for Unmanned Aerial Vehicle …
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GPS-LiDAR sensor fusion aided by 3D city models for UAVs
… of the UAV. Light Detection and Ranging (LiDAR), one such sensor, provides a real-time point cloud of its surroundings. In a dense urban environment, LiDAR is able to detect a large number of features of surrounding structures, such as buildings, as opposed to in an open-sky environment. …
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Automated segmentation, detection and fitting of piping elements from terrestrial LIDAR data
… the invention of light detection and ranging (LIDAR) in the early 1960s, it has been adopted for use in numerous applications, from topographical mapping with airborne LIDAR platforms to surveying of urban sites with terrestrial LIDAR systems. Static terrestrial LIDAR has become an especially …
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Improving Tree Crown Mapping using Airborne LiDAR with Genetic Algorithms
… mapping of individual trees derived from LiDAR (Light Detection And Ranging) data have been found to be valuable for a wide range of environmental analyses including carbon inventories; fuel estimations for wildfire risk assessment and management. These mapping efforts use individual tree …
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Multirotor UAS Sense and Avoid with Sensor Fusion
… comprised of a 3D Light Detection and Ranging (LIDAR) sensor, visual camera, and 9 Degree of Freedom (DOF) Inertial Measurement Unit (IMU) was found to be beneficial to autonomous UAS SAA in urban environments. Promising results are based on to the broadening of available information about a …
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Novel Methods based on the Fusion of Multisensor Remote Sensing Data for Accurate Forest Parameter Estimation
… forest by using very high-density multireturn LiDAR data. The aim of the proposed method is to fully exploit the potential of these data to detect and delineate the single tree crowns of both dominant and sub-dominant trees by a hierarchical 3-D segmentation technique applied directly in the …
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Towards Systematic Selection of Terrain- and Ground Cover-Specific LiDAR Filtering Parameters
<p>Accurate automated classification of LiDAR point clouds is a well-known problem and proper parameterization of the classification algorithm is essential to creating useful bare-earth terrain models. Parameterization is particularly important in areas characterized by extremely low relief, such …
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Development and analysis of a small-scale controlled dataset with various weather conditions, lighting, and route types for autonomous driving
… to collect 360-degree image information and LiDAR point clouds at 10Hz. Due to the constraints of time and resources, we used algorithmic prediction to generate ground truth data via the Co-DETR 2D prediction algorithm. We validated the accuracy of the Co-DETR algorithm through partial manual …
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DEEP-LEARNING LOCAL FEATURES FOR PHOTOGRAMMETRIC APPLICATIONS AND VISUAL POSITIONING
… 2) multi-modal matching between RGB images and LiDAR point clouds; 3) matching off-track satellite images for 3D reconstruction and change detection; 4) precise positioning in GNSS-denied environments. In the PhD work, new workflows and processing methods have been implemented and validated …
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ECO-LENS Addressing Urban Biodiversity with Machine Learning
… tools in the form of satellite imagery and LiDAR enables extensive coverage of urban areas, providing an opportunity to evaluate biodiversity patterns across entire regions without causing disturbance to ecosystems. While remote sensing has significantly improved our capacity to monitor …
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Image Analysis Techniques for LiDAR Point Cloud Segmentation and Surface Estimation
Light Detection And Ranging (LiDAR), as well as many other applications and sensors, involve segmenting sparse sets of points (point clouds) for which point density is the only discriminating feature. The segmentation of these point clouds is challenging for several reasons, including the fact that …
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Decision Support for Operational Plantation Forest Inventories through Auxiliary Information and Simulation
… incorporation of light detection and ranging (lidar) and thinning status improved the precision of inventory estimates compared with ground data alone. Further investigation found that reduced density lidar point clouds and lower resolution elevation models could be used to generate estimates …
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Estimating pre-fire forest structure with stereo imagery and post-fire lidar
Lidar has become an established tool for mapping forest structure attributes including those used as inputs for fire behavior and effects modelling. However, lidar is rarely available to document pre-fire conditions due to its sparse availability. In contrast, aerial imagery is regularly collected …
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Neural Representation for 3D Building Reconstruction from Point Clouds
… has underscored the importance of airborne LiDAR point clouds (APCs) for efficient/cost effective urban planning, management, and development. However, the delineation and modeling of 3D objects -- specifically buildings -- from APCs pose significant challenges due to issues such as …
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Graphical SLAM for urban UAV navigation
… sensors, such as Light Detection and Ranging (LiDAR) sensors. LiDAR-based odometry provides an accurate relative navigation solution in GPS-challenged environments, but requires distinguishable features in the surrounding environment and is susceptible to drift and biases. As a result, there is …
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Fusion of Full Waveform LiDAR and Passive Remote Sensing for Improved Land-Cover Classification
… spatial and spectral domains. On the other hand, LiDAR (Light Detection And Ranging) data has gained increasing interest for use in classification because it provides precise three-dimensional (3-D) data for large areas with precise 3-D location information, and therefore greatly expands the …
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Mapping of complex marine environments using an unmanned surface craft
… extensive sensor suite that includes three SICK lidars, a Blueview MB2250 imaging sonar, a Doppler Velocity Log, and an integrated global positioning system/inertial measurement unit (GPS/IMU) device. The data from these sensors is processed in a hybrid metric/topological SLAM state estimation …
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River channel dynamics mapped with dense lidar point cloud time series
… high-resolution airplane- and drone-based lidar datasets that describe the detailed shape of the bank surface topography. Changes between the datasets show how the outer channel banks evolve over time scales ranging from two months to 14 years. A second motivation for my work is to advance …
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