Results 51 to 60 of about 6,825,217 (303)
Machining tool identification utilizing temporal 3D point clouds [PDF]
, 2023 The manufacturing domain is regarded as one of the most important engineering areas. Recently, smart manufacturing merges the use of sensors, intelligent controls, and software to manage each stage in the manufacturing lifecycle.
Zoumpekas, Thanasis +5 more
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CLASSIFICATION OF AERIAL PHOTOGRAMMETRIC 3D POINT CLOUDS [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2017 Abstract. We present a powerful method to extract per-point semantic class labels from aerial photogrammetry data. Labelling this kind of data is important for tasks such as environmental modelling, object classification and scene understanding. Unlike previous point cloud classification methods that rely exclusively on geometric features, we show that
C. Becker +4 more
openaire +4 more sources
3D Point Cloud Recognition Based on a Multi-View Convolutional Neural Network
Sensors, 2018 The recognition of three-dimensional (3D) lidar (light detection and ranging) point clouds remains a significant issue in point cloud processing. Traditional point cloud recognition employs the 3D point clouds from the whole object.
Le Zhang, Jian Sun, Qiang Zheng
doaj +1 more source
Point attention network for semantic segmentation of 3D point clouds [PDF]
Pattern Recognition, 2020 Submitted to a ...
Mingtao Feng +4 more
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Adversarial Shape Perturbations on 3D Point Clouds [PDF]
, 2020 18 pages, accepted to the 2020 ECCV workshop on Adversarial Robustness in the Real World, source code available at this https url: https://github.com/Daniel-Liu-c0deb0t/Adversarial-point-perturbations-on-3D ...
Daniel Liu, Ronald Yu, Hao Su 0001
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Advanced Engineering Materials, Volume 27, Issue 6, March 2025.The stability criteria affecting the formation of high‐entropy alloys, particularly focusing in supersaturated solid solutions produced by mechanical alloying, are analyzed. Criteria based on Hume–Rothery rules are distinguished from those derived from thermodynamic relations. The formers are generally applicable to mechanically alloyed samples.
Javier S. Blázquez +5 more
wiley +1 more source
Feature Visualization for 3D Point Cloud Autoencoders
2020 International Joint Conference on Neural Networks (IJCNN), 2020 In order to reduce the dimensionality of 3D point cloud representations, autoencoder architectures generate increasingly abstract, compressed features of the input data. Visualizing these features is central to understanding the learning process, however, while successful visualization techniques exist for neural networks applied to computer vision ...
Thiago Rios +5 more
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Advances in Sustainable and Wearable Textile Based Soft Robotics
Advanced Functional Materials, EarlyView.This Review examines advances in wearable textile‐based soft robotics, focusing on sustainable materials, integrated sensing, and scalable actuation. It discusses manufacturing and system integration across healthcare, assistive robotics, prosthetics, and human–machine interfaces, and highlights key challenges in circular design, including life‐cycle ...
Zahir Abbas +6 more
wiley +1 more source
Global Journal of Engineering and Technology Advances, 2023 A collection of multidimensional points is represented by a data structure called a point cloud, which is frequently used to describe 3-D data. A point cloud is, technically speaking, a database of points in a three-dimensional coordinate system. However, from the viewpoint of a typical workflow, the only thing that matters is that a point cloud is an ...
Roopa B S +3 more
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3D DATA ACQUISITION FOR INDOOR ASSETS USING TERRESTRIAL LASER SCANNING [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2013 The newly development of technology clearly shows an improvement of three-dimension (3D) data acquisition techniques. The requirements of 3D information and features have been obviously increased during past few years in many related fields.
S. Y. Lee, Z. Majid, H. Setan
doaj +1 more source