Results 321 to 330 of about 5,619,317 (360)
Some of the next articles are maybe not open access.
Analytical Chemistry, 2021
Respective detection of microplastics (MPs) and nanoplastics (NPs) is of great importance for their different environmental behaviors and toxicities. Using spherical polystyrene (PS) and poly(methyl methacrylate) (PMMA) plastics as models, the efficiency
Qing-cun Li +8 more
semanticscholar +1 more source
Respective detection of microplastics (MPs) and nanoplastics (NPs) is of great importance for their different environmental behaviors and toxicities. Using spherical polystyrene (PS) and poly(methyl methacrylate) (PMMA) plastics as models, the efficiency
Qing-cun Li +8 more
semanticscholar +1 more source
Point cloud filtering on UAV based point cloud
Measurement, 2019Abstract Nowadays, Unmanned Aerial Vehicles (UAVs) have been attracted wide attentions such as a new measurement equipment and mapping, which are capable of the high-resolution point cloud data collection. In addition, a massive point cloud data has brought about the data filtering and irregular data organization for the generation of digital terrain
İsmail Şanlıoğlu +2 more
openaire +3 more sources
On the Visibility of Point Clouds
2015 IEEE International Conference on Computer Vision (ICCV), 2015Is it possible to determine the visible subset of points directly from a given point cloud? Interestingly, in [7] it was shown that this is indeed the case - despite the fact that points cannot occlude each other, this task can be performed without surface reconstruction or normal estimation. The operator is very simple - it first transforms the points
Ayellet Tal, Sagi Katz
openaire +2 more sources
Inverse Problems in Science and Engineering, 2011
A method based on point cloud smoothing approaches for detecting noise and outliers is introduced. This method firstly estimates thresholds according to points’ shifts after smoothing, secondly identifies outliers and noise whose shifts are more than the thresholds and lastly removes them and repeats the whole process.
Mingyue Ding, Wenguang Hou, Taiwai Chan
openaire +2 more sources
A method based on point cloud smoothing approaches for detecting noise and outliers is introduced. This method firstly estimates thresholds according to points’ shifts after smoothing, secondly identifies outliers and noise whose shifts are more than the thresholds and lastly removes them and repeats the whole process.
Mingyue Ding, Wenguang Hou, Taiwai Chan
openaire +2 more sources
Application of Improved Point Cloud Streamlining Algorithm in Point Cloud Registration [PDF]
2020 Chinese Control And Decision Conference (CCDC), 2020 Collect point cloud data of objects with commonly used 3D scanning equipment, the resulting point cloud data is huge. Traditional point cloud registration algorithms cannot guarantee both efficiency and accuracy. To this end, combining octree-based K-means clustering point cloud streamlining algorithm with an ICP algorithm with improved weight ratio ...
Guo Xifeng +3 more
openaire +1 more source
PointMamba: A Simple State Space Model for Point Cloud Analysis
Neural Information Processing SystemsTransformers have become one of the foundational architectures in point cloud analysis tasks due to their excellent global modeling ability. However, the attention mechanism has quadratic complexity, making the design of a linear complexity method with ...
Dingkang Liang +7 more
semanticscholar +1 more source
Proceedings of the 2004 Eurographics/ACM SIGGRAPH symposium on Geometry processing, 2004
Point clouds are one of the most primitive and fundamental surface representations. A popular source of point clouds are three dimensional shape acquisition devices such as laser range scanners. Another important field where point clouds are found is in the representation of high-dimensional manifolds by samples. With the increasing popularity and very
Guillermo Sapiro, Facundo Mémoli
openaire +2 more sources
Point clouds are one of the most primitive and fundamental surface representations. A popular source of point clouds are three dimensional shape acquisition devices such as laser range scanners. Another important field where point clouds are found is in the representation of high-dimensional manifolds by samples. With the increasing popularity and very
Guillermo Sapiro, Facundo Mémoli
openaire +2 more sources
Point clouds and Hydroinformatics
2022<p>Point cloud is made up of a multitude of three-dimensional (3D) points with one or more attributes attached. Point cloud is the third data paradigm in addition to the well-established object (vector) and gridded (raster) representations, since point cloud data can be directly collected, computed, stored, and analyzed without converting
Vitali Diaz +7 more
openaire +2 more sources
arXiv.org
Recently, state space model (SSM) has gained great attention due to its promising performance, linear complexity, and long sequence modeling ability in both language and image domains.
Jiuming Liu +6 more
semanticscholar +1 more source
Recently, state space model (SSM) has gained great attention due to its promising performance, linear complexity, and long sequence modeling ability in both language and image domains.
Jiuming Liu +6 more
semanticscholar +1 more source
Self-Supervised Intra-Modal and Cross-Modal Contrastive Learning for Point Cloud Understanding
IEEE transactions on multimediaLearning effective representations from unlabeled data is a challenging task for point cloud understanding. As the human visual system can map concepts learned from 2D images to the 3D world, and inspired by recent multimodal research, we introduce data ...
Yue Wu +7 more
semanticscholar +1 more source