Results 61 to 70 of about 107,458 (327)

A Point Cloud Segmentation Method for Dim and Cluttered Underground Tunnel Scenes Based on the Segment Anything Model

Remote Sensing, 2023
In recent years, point cloud segmentation technology has increasingly played a pivotal role in tunnel construction and maintenance. Currently, traditional methods for segmenting point clouds in tunnel scenes often rely on a multitude of attribute ...
Jitong Kang, Ning Chen, Mei Li, Shanjun Mao, Haoyuan Zhang, Yingbo Fan, Hui Liu   +6 more
doaj   +1 more source

Revisiting Stability Criteria in Ball‐Milled High‐Entropy Alloys: Do Hume–Rothery and Thermodynamic Rules Equally Apply?

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, Alejandro F. Manchón‐Gordón, Antonio Vidal‐Crespo, Rafael Caballero‐Flores, Jhon J. Ipus, Clara F. Conde   +5 more
wiley   +1 more source

Deep-Learning-Based Semantic Segmentation Approach for Point Clouds of Extra-High-Voltage Transmission Lines

Remote Sensing, 2023
The accurate semantic segmentation of point cloud data is the basis for their application in the inspection of extra high-voltage transmission lines (EHVTL).
Hao Yu, Zhengyang Wang, Qingjie Zhou, Yuxuan Ma, Zhuo Wang, Huan Liu, Chunqing Ran, Shengli Wang, Xinghua Zhou, Xiaobo Zhang   +9 more
doaj   +1 more source

Surface Tension Measurement of Ti‐6Al‐4V by Falling Droplet Method in Oxygen‐Free Atmosphere

Advanced Engineering Materials, EarlyView.
In this article, the temperature‐dependent surface tension of free falling, oscillating Ti‐6Al‐4V droplets is investigated in both argon and monosilane doped, oxygen‐free atmosphere. Droplet temperature and oscillation are captured with one single high‐speed camera, and the surface tension is calculated with Rayleigh's formula.
Johannes May, Finn‐Lennard Janthur, Lena Kreie, Michael Müller, Sarah Seffer, Nick Schwarz, Jörg Hermsdorf, Thomas Hassel, Stefan Kaierle, Ludger Overmeyer   +9 more
wiley   +1 more source

A Lightweight Procedural Layer for Hybrid Experimental–Computational Workflows in Materials Science

Advanced Engineering Materials, EarlyView.
We unveil a prototype hybrid‐workflow framework that fuses automatedcomputation with hands‐on experiments. Built atop pyiron, a lightweight, parameterized layer translates procedure descriptions into executable manual steps, syncing instrument settings, human interventions, and data capture in real‐time today.
Steffen Brinckmann, Sarath Menon, Raphael Röske, Johannes Steinhülb, Michael Selzer, Jan Janssen, Tilmann Hickel, Ruth Schwaiger, Jörg Neugebauer   +8 more
wiley   +1 more source

Adaptive Clustering for Point Cloud

Sensors
The point cloud segmentation method plays an important role in practical applications, such as remote sensing, mobile robots, and 3D modeling. However, there are still some limitations to the current point cloud data segmentation method when applied to ...
Zitao Lin, Chuanli Kang, Siyi Wu, Xuanhao Li, Lei Cai, Dan Zhang, Shiwei Wang   +6 more
doaj   +1 more source

SoftGroup for 3D Instance Segmentation on Point Clouds [PDF]

, 2022
Thang X. Vu, Kookhoi Kim, Tung M. Luu, Xuân Thanh Nguyễn, Chang D. Yoo   +4 more
openalex   +1 more source

CNN for Very Fast Ground Segmentation in Velodyne LiDAR Data

, 2017
This paper presents a novel method for ground segmentation in Velodyne point clouds. We propose an encoding of sparse 3D data from the Velodyne sensor suitable for training a convolutional neural network (CNN).
Herout, Adam, Hradis, Michal, Spanel, Michal, Velas, Martin   +3 more
core   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Filtering-Assisted Airborne Point Cloud Semantic Segmentation for Transmission Lines

Sensors
Point cloud semantic segmentation is crucial for identifying and analyzing transmission lines. Due to the number of point clouds being huge, complex scenes, and unbalanced sample proportion, the mainstream machine learning methods of point cloud ...
Wanjing Yan, Weifeng Ma, Xiaodong Wu, Chong Wang, Jianpeng Zhang, Yuncheng Deng   +5 more
doaj   +1 more source