The Chinese Ocean Salinity Mission (COSM) is an ocean observation mission performed by the National Satellite Ocean Application Service (NSOAS), China Academy of Space Technology (CAST) and National Space Science Center (NSSC). It is the first satell...
To investigate the influence of segmental lining width on ground and tunnel deformation during shield tunneling beneath residential buildings, a numerical analysis model was established using Midas GTS NX based on the engineering context of the Guang...
Compared with straight tunnels, over-excavation occurs on the inner side of the curved section during shield construction of small radius curved tunnels, and the disturbance to the ground surface and mechanical properties of surrounding rock and segm...
When the power-frequency short-circuit current flows through the armor rods segment on an overhead ground wire (OGW), the OGW at the segment may experience fracture failure due to high temperatures. Consequently, it is necessary to optimize the struc...
The operation of microgravity research missions, such as sounding rockets, CubeSats, and small landers, typically relies on proprietary mission control infrastructures, which limit reproducibility, portability, and interdisciplinary use. In this work...
Satellite ground segments run conventional, patchable software, but disruptive maintenance must be coordinated with recurring orbital visibility. We formulate vulnerability remediation as a constrained action-and-timing problem in which SGP4-propagat...
We propose a completely unsupervised approach to simultaneously estimate scene depth, ego-pose, ground segmentation and ground normal vector from only monocular RGB video sequences. In our approach, estimation for different scene structures can mutua...
Referring Remote Sensing Image Segmentation (RRSIS) is a representative multimodal understanding task for remote sensing, which segments designated targets from remote images according to free-form natural language descriptions. However, complex remo...
Ground segmentation is a crucial task in the field of 3D LiDAR perception for autonomous driving. It is commonly used as a preprocessing step for tasks such as object detection and road extraction. However, the existing ground segmentation algorithms...
Robust and precise vehicle detection is the prerequisite for decision-making and motion planning in autonomous driving. Vehicle detection algorithms follow three steps: ground segmentation, obstacle clustering and bounding box fitting. The ground seg...
Solar irradiance is one of the main factors affecting the output of photovoltaic power stations. The cloud distribution above the photovoltaic power station can determine the strength of the absorbed solar irradiance. Cloud estimation is another impo...
In the final approach stage of rendezvous and docking of a spacecraft, the pose parameters of the target spacecraft need to meet docking or berthing capture conditions. Visible light visual measurement systems are increasingly employed in spacecraft...
Taking the segmented utility tunnel crossing f5 ground fissures in Xi’an Xingfu forest belt as the research object, this paper investigates the acceleration response and the variation of displacement and stress of the segmented utility tunnel u...
Ground segmentation is an essential preprocessing step for LiDAR-based perception in autonomous driving, as it directly affects subsequent object clustering and obstacle detection. This paper proposes a fast grid-based ground segmentation method for...
Mobile robot operators must make rapid decisions based on information about the robot’s surrounding environment. This means that terrain modeling and photorealistic visualization are required for the remote operation of mobile robots. We have produce...
The shield tunneling method is widely used, especially in urban areas, since it is efficient for minimizing disturbances to surroundings. Although segmental lining is commonly used in this method, in both the research and practice of tunnel lining de...
Ground-based cloud images contain a wealth of cloud information and are an important part of meteorological research. However, in practice, ground cloud images must be segmented and classified to obtain the cloud volume, cloud type and cloud coverage...
Background. Efficient analysis of large image data produced in greenhouse phenotyping experiments is often challenged by a large variability of optical plant and background appearance which requires advanced classification model methods and reliable...
In the near future, autonomous vehicles with full self-driving features will populate our public roads. However, fully autonomous cars will require robust perception systems to safely navigate the environment, which includes cameras, RADAR devices, a...
Cloud image segmentation is a technique that divides images captured by meteorological satellites or ground-based observations into different regions or categories. By extracting the distribution, shape, and dynamic features of clouds, it provides pr...
Ground-based hyperspectral imaging extends remote sensing to road environments by providing material-sensitive spectra for distinguishing visually similar surfaces and objects. However, pixel-wise prediction from high-dimensional spectral cubes is co...
Chest radiographs come with abundant free-text reports but scarce lesion-level annotation, so report text increasingly supervises localization. This structured narrative review, written for model developers, benchmark curators, and evaluators of clin...
LiDAR occupies a vital position in self-driving as the advanced detection technology enables autonomous vehicles (AVs) to obtain much environmental information. Ground segmentation for LiDAR point cloud is a crucial procedure to ensure AVs’ driving s...
This paper investigates the application of image segmentation techniques in endodontics, focusing on improving diagnostic accuracy and achieving faster segmentation by delineating specific dental regions such as teeth and root canals. Deep learning a...
Rubber trees in southern China are often impacted by natural disturbances that can result in a tilted tree body. Accurate crown segmentation for individual rubber trees from scanned point clouds is an essential prerequisite for accurate tree paramete...
Photovoltaic (PV) inventories with explicit location and extent are needed for energy accounting, distribution-grid planning, and asset monitoring. However, the ground sampling distance (GSD) of different sources spans nearly an order of magnitude, s...
Rubber trees in southern China are often impacted by natural disturbances, and accurate rubber tree crown segmentation and property retrieval are of great significance for forest cultivation treatments and silvicultural risk management. Here, three p...
Ground segmentation in LiDAR point clouds is a foundational capability for autonomous systems, enabling safe navigation in applications ranging from urban self-driving vehicles to planetary exploration rovers. Reliably distinguishing traversable surf...
MERLIN (MEthane Remote sensing LIdar missioN) is a Franco-German space mission designed to provide weighted columns of atmospheric methane through an inversion of the lidar signal using a priori information on the atmospheric state. Uncertainties abo...
This paper presents the design, optimization, and performance evaluation of a Satellite-Based Augmentation System (SBAS) ground segment tailored to Colombia’s air navigation infrastructure, with emphasis on ionospheric anomalies in equatorial l...
Growth monitoring of crops is a crucial aspect of precision agriculture, essential for optimal yield prediction and resource allocation. Traditional crop growth monitoring methods are labor-intensive and prone to errors. This study introduces an auto...
Background: Accurate ground segmentation in 3D point clouds is critical for robotic perception, enabling robust navigation, object detection, and environmental mapping. However, existing methods struggle with over-segmentation, under-segmentation, an...
In the field of medical imaging, the division of an image into meaningful structures using image segmentation is an essential step for pre-processing analysis. Many studies have been carried out to solve the general problem of the evaluation of image...
Mangrove forests provide valuable ecosystem services to coastal communities across tropical and subtropical regions. Current anthropogenic stressors threaten these ecosystems and urge researchers to create improved monitoring methods for better envir...
3D object-detection based on LiDAR point clouds can help driverless vehicles detect obstacles. However, the existing point-cloud-based object-detection methods are generally ineffective in detecting small objects such as pedestrians and cyclists. The...
Robust and quick road curb detection under various situations is critical in developing intelligent vehicles. However, the road curb detection is easily affected by the obstacles in the road area when Lidar based method is applied. A practical road c...
We investigated how midfoot stiffness of running shoes influences foot segment kinematics and ground reaction force (GRF) during heel-toe running. Nineteen male rearfoot strike runners performed overground heel-toe running at 3.3 m/s when wearing sho...
Hematoma expansion (HE) is an independent predictor of poor outcomes and a modifiable treatment target in intracerebral hemorrhage (ICH). Evaluating HE in large datasets requires segmentation of hematomas on admission and follow-up CT scans, a proces...
A Mw7.8 earthquake struck Turkey on 6 February 2023, causing severe casualties and economic losses. This paper investigates the characteristics of strong ground motion and seismogenic fault of the earthquake. We collected and processed the strong gro...
Injecting grout into the gaps between tunnel shield segments and surrounding rocks can reduce ground subsidence and prevent ground water penetration. However, insufficient grouting and grouting defects may cause serious geological disasters. Ground p...
Herein, we propose a novel indoor structure extraction (ISE) method that can reconstruct an indoor planar structure with a feature structure map (FSM) and enable indoor robot navigation using a navigation structure map (NSM). To construct the FSM, we...
Image segmentation is a crucial step of almost any Digital Rock workflow. In this paper, we propose an approach for generation of a labelled dataset and investigate an application of three popular convolutional neural networks (CNN) architectures for...
Localization and mapping are key requirements for autonomous mobile systems to perform navigation and interaction tasks. Iterative Closest Point (ICP) is widely applied for LiDAR scan-matching in the robotic community. In addition, the standard ICP a...
Over the past three decades, five satellites have succeeded one another on the reference orbit, building the longest continuous climate record of global sea level measurements. Its continuity is ensured thanks to tandem flights between consecutive sa...
The integration of satellite data with deep learning has revolutionized various tasks in remote sensing, including classification, object detection, and semantic segmentation. Cloud segmentation in high-resolution satellite imagery is a critical appl...
Facial skin analysis has attracted considerable attention in the skin health domain. The results of facial skin analysis can be used to provide skin care and cosmetic recommendations in aesthetic dermatology. Because of the existence of several skin...
All-sky imaging systems are currently very popular. They are used in ground-based meteorological stations and as a crucial part of the weather monitors for autonomous robotic telescopes. Data from all-sky imaging cameras provide important information...
Thermal infrared (TIR) whole-sky imaging enables continuous cloud observations during both daytime and nighttime, making it an important tool for ground-based cloud monitoring. However, existing infrared cloud detection methods mainly rely on manuall...
As the amount of ground-penetrating radar (GPR) data increases significantly with the high demands of nondestructive detection methods under urban roads, a method suitable for time-lapse data dynamic monitoring should be developed to quickly identify...
Using multiple cameras with force platforms is a classical and popular method for gait analysis. However; it is difficult to measure natural walking; because the subjects have to adjust their steps to place on the force platform. This study proposes...
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