Results 71 to 80 of about 7,018 (281)

Trigonometric words ranking model for spam message classification

IET Networks, EarlyView., 2022
Abstract The significant increase in the volume of fake (spam) messages has led to an urgent need to develop and implement a robust anti‐spam method. Several of the current anti‐spam systems depend mainly on the word order of the message in determining the spam message, which results in the system's inability to predict the correct type of message when
Suha Mohammed Hadi, Ali Hakem Alsaeedi, Dhiah Al‐Shammary, Zaid Abdi Alkareem Alyasseri, Mazin Abed Mohammed, Karrar Hameed Abdulkareem, Riyadh Rahef Nuiaa, Mustafa Musa Jaber   +7 more
wiley   +1 more source

POINT CLOUD SEGMENTATION AND SEMANTIC ANNOTATION AIDED BY GIS DATA FOR HERITAGE COMPLEXES [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2019
Point cloud segmentation is an important first step in categorising a raw point cloud data. This step is necessary in order to better manage the data and generate other derivative products, e.g. 3D GIS or HBIM.
A. Murtiyoso, P. Grussenmeyer
doaj   +1 more source

An Efficient Ensemble Deep Learning Approach for Semantic Point Cloud Segmentation Based on 3D Geometric Features and Range Images

Sensors, 2022
Mobile light detection and ranging (LiDAR) sensor point clouds are used in many fields such as road network management, architecture and urban planning, and 3D High Definition (HD) city maps for autonomous vehicles.
Muhammed Enes Atik, Zaide Duran
doaj   +1 more source

Learning‐Based Soft Robotic Grasping: Recent Progress and Remaining Challenges

Advanced Robotics Research, EarlyView.
This review analyzes learning‐based soft robotic grasping from a pipeline‐oriented perspective, encompassing soft gripper design, multimodal sensing, and learning‐based planning and control. It surveys key neural network architectures and benchmark datasets and identifies critical challenges such as sim‐to‐real transfer, generalization, and continual ...
Arnab Majumder, Jelizaveta Konstantinova, Graham Deacon, Kaspar Althoefer   +3 more
wiley   +1 more source

RWAFormer: a lightweight road LiDAR point cloud segmentation network based on transformer

Frontiers in Computer Science
Point cloud semantic segmentation technology for road scenes plays an important role in the field of autonomous driving. However, accurate semantic segmentation of large-scale and non-uniformly dense LiDAR road point clouds still faces severe challenges.
Zirui Li, Lei Chen, Ying Liu, Shuang Zhao, Qinghe Guan   +4 more
doaj   +1 more source

When Biology Meets Medicine: A Perspective on Foundation Models

Advanced Intelligent Discovery, EarlyView.
Artificial intelligence, and foundation models in particular, are transforming life sciences and medicine. This perspective reviews biological and medical foundation models across scales, highlighting key challenges in data availability, model evaluation, and architectural design.
Kunying Niu, Yuxing Wang, Limin Zou, Jing Huang   +3 more
wiley   +1 more source

Large-Scale Point Cloud Semantic Segmentation with Superpoint Graphs [PDF]

2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018
Accepted to CVPR 2018; camera ready version. Major updates to [v1]: Improved performance on S3DIS (from +5.8 to +12.4 mIoU) and extended ablation study in ...
Landrieu, Loic, Martin, Simonovsky
openaire   +4 more sources

JSMNet Improving Indoor Point Cloud Semantic and Instance Segmentation through Self-Attention and Multiscale [PDF]

, 2023
The semantic understanding of indoor 3D point cloud data is crucial for a range of subsequent applications, including indoor service robots, navigation systems, and digital twin engineering. Global features are crucial for achieving high-quality semantic
Xu, Shuochen, Zhang, Zhenxin
core   +1 more source

An Onboard Point Cloud Semantic Segmentation System for Robotic Platforms [PDF]

, 2023
Point clouds represent an important way for robots to perceive their environments, and can be acquired by mobile robots with LiDAR sensors or underwater robots with sonar sensors.
Jingchun Zhou, Yujie Yang, Fei Wang, Weishi Zhang   +3 more
core   +1 more source

Human‐in‐the‐Loop Object Segmentation for 3D Gaussian Splatting via Finger‐based VR Interface

Advanced Intelligent Systems, EarlyView.
This study introduces a human‐in‐the‐loop segmentation framework for 3D Gaussian Splatting that integrates real‐time optimization with intuitive VR‐based finger prompting. Compared with existing automatic, learning‐based methods, it achieves significantly higher accuracy and reduced segmentation time.
Yongseok Lee, Hyunreal Park, Hyunsu Kim, Harim Ji, Dongho Yee, Dongjun Lee   +5 more
wiley   +1 more source