Results 21 to 30 of about 45,895 (267)
3D‐FEGNet: A feature enhanced point cloud generation network from a single image
IET Computer Vision, 2023 Deep learning‐based single view 3D reconstruction is a hot topic in computer vision. However, predicting a more realistic 3D point cloud from a single image is an ill‐posed problem.
Ende Wang +4 more
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GSV-NET: A Multi-Modal Deep Learning Network for 3D Point Cloud Classification
Applied Sciences, 2022 Light Detection and Ranging (LiDAR), which applies light in the formation of a pulsed laser to estimate the distance between the LiDAR sensor and objects, is an effective remote sensing technology.
Long Hoang +3 more
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SEMANTIC ENRICHMENT OF 3D POINT CLOUDS USING 2D IMAGE SEGMENTATION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2023 3D point cloud segmentation is computationally intensive due to the lack of inherent structural information and the unstructured nature of the point cloud data, which hinders the identification and connection of neighboring points.
A. Rai +3 more
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Remote Sensing, 2020 The preference of three-dimensional representation of underground cable wells from two-dimensional symbols is a developing trend, and three-dimensional (3D) point cloud data is widely used due to its high precision.
Ming Huang +4 more
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3D point cloud lossy compression using quadric surfaces [PDF]
PeerJ Computer Science, 2021 The presence of 3D sensors in hand-held or head-mounted smart devices has motivated many researchers around the globe to devise algorithms to manage 3D point cloud data efficiently and economically. This paper presents a novel lossy compression technique
Ulfat Imdad +3 more
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Generating 3D point-cloud based on combining adjacent multi-station scanning data in 2D laser scanning: A case study of Hokuyo UTM 30lxk [PDF]
Archives of Civil Engineering, 2021 Using a lower-cost laser scanner for generating accuracy in 3D point-cloud has been a concern because of economic issues; therefore, this study aims to create a 3D point cloud of a target object using a low-cost 2D laser scanner, Hokuyo UTM 30LX.
Anh Thu Thi Phan, Ngoc Thi Huynh
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3D point cloud recognition of substation equipment based on plane detection
Results in Engineering, 2022 Substation equipment identification is a key step in the process of intelligent substation designing. The target recognition of 3D point cloud of substation equipment firstly uses a 3D laser scanner to obtain the 3D point cloud data that can express the ...
Qianjin Yuan, Yong Luo, HeShan Wang
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Deep Learning Based Point Cloud Processing Techniques
IEEE Access, 2022 In this study, deep learning techniques and algorithms used in point cloud processing have been analysed. Methods, technical properties and algorithms developed for 3D Object Classification and Segmentation, 3D object detection and tracking and 3D scene ...
Abdurrahman Hazer, Remzi Yildirim
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Sensors, 2023 Structured light technology is typical for capturing 3D point cloud data. This paper proposes a 3D reconstruction system to obtain point cloud data of complex objects based on nine-order Gray code and an eight-step structured light projection combined ...
Yun Feng +3 more
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Machine Learning in LiDAR 3D Point Clouds [PDF]
, 2021 LiDAR point clouds contain measurements of complicated natural scenes and can be used to update digital elevation models, glacial monitoring, detecting faults and measuring uplift detecting, forest inventory, detect shoreline and beach volume changes, landslide risk analysis, habitat mapping, and urban development, among others.
F. Patricia Medina, Randy C. Paffenroth
openaire +2 more sources