Results 111 to 120 of about 6,440,801 (359)
Relation-Shape Convolutional Neural Network for Point Cloud Analysis [PDF]
Computer Vision and Pattern Recognition, 2019 Point cloud analysis is very challenging, as the shape implied in irregular points is difficult to capture. In this paper, we propose RS-CNN, namely, Relation-Shape Convolutional Neural Network, which extends regular grid CNN to irregular configuration ...
Yongcheng Liu +3 more
semanticscholar +1 more source
, 2018 Generative Adversarial Networks (GAN) can achieve promising performance on learning complex data distributions on different types of data. In this paper, we first show a straightforward extension of existing GAN algorithm is not applicable to point clouds, because the constraint required for discriminators is undefined for set data.
Li, Chun-Liang +4 more
openaire +2 more sources
Advanced Engineering Materials, EarlyView.Primary phases and a fatigue crack are studied in a forged blank of an aluminum alloy using synchrotron and laboratory X‐ray computed tomography. To image the crack, the fatigue test is interrupted, and a static tensile load is applied to open the crack.
Jakob Schröder +6 more
wiley +1 more source
Data-Driven Point Cloud Objects Completion
Sensors, 2019 With the development of the laser scanning technique, it is easier to obtain 3D large-scale scene rapidly. However, many scanned objects may suffer serious incompletion caused by the scanning angles or occlusion, which has severely impacted their future ...
Yang Zhang, Zhen Liu, Xiang Li, Yu Zang
doaj +1 more source
Deep Closest Point: Learning Representations for Point Cloud Registration [PDF]
IEEE International Conference on Computer Vision, 2019 Point cloud registration is a key problem for computer vision applied to robotics, medical imaging, and other applications. This problem involves finding a rigid transformation from one point cloud into another so that they align. Iterative Closest Point
Yue Wang, J. Solomon
semanticscholar +1 more source
The Bilateral Filter for Point Clouds [PDF]
Image Processing On Line, 2017 Point sets obtained by 3D scanners are often corrupted with noise, that can have several causes, such as a tangential acquisition direction, changing environmental lights or a reflective object material. It is thus crucial to design efficient tools to remove noise from the acquired data without removing important information such as sharp edges or ...
Digne, Julie, de Franchis, Carlo
openaire +2 more sources
Advanced Engineering Materials, EarlyView.A multimaterial approach is introduced to improve upon auxetic structures by combining two different polymers into the same reentrant honeycomb structure via additive manufacturing. The deformation behavior as well as the resulting Poisson's ratio are thereby improved significantly.
Alexander Engel +2 more
wiley +1 more source
TE Wave Measurement and Modeling
, 2013 In the TE wave method, microwaves are coupled into the beam-pipe and the effect of the electron cloud on these microwaves is measured. An electron cloud (EC) density can then be calculated from this measurement.
Alesini, David +4 more
core +1 more source
Advanced Functional Materials, Volume 35, Issue 12, March 18, 2025.The formate pseudo‐halide anion is strategically introduced at the buried interface to stabilize the intermediate phases formed during perovskite crystallization. The controlled crystallization enhances crystallinity and alleviates tensile strain, eliminating residual PbI2 near the buried interface.
Jongdeuk Seo +12 more
wiley +1 more source
Advanced Functional Materials, Volume 35, Issue 12, March 18, 2025.In this study, the unique role of the unusual lone‐pair‐π conjugation mechanism in poly(1,4‐anthraquinone) (P14AQ) is explored as an organic electrode material. Unlike traditional π‐π interactions, P14AQ's conjugation involves lone pairs of oxygen atoms interacting with the π cloud of adjacent units, enabling stable charge transport even with minimal π‐
Xiaotong Zhang, Piotr de Silva
wiley +1 more source