您当前的位置：
首页 >
文章列表页 >
Part segmentation method of point cloud considering optimal allocation and optimal mask
Information Sciences | 更新时间：2024-07-26
|

    • Part segmentation method of point cloud considering optimal allocation and optimal mask

    • “In the field of point cloud component segmentation, researchers have proposed a new method that improves segmentation accuracy through optimal allocation and optimal masking, effectively enhancing the network's generalization ability.”
    • Optics and Precision Engineering   Vol. 32, Issue 12, Pages: 1941-1953(2024)

    • DOI：10.37188/OPE.20243212.1941    

      CLC： TP394.1;TH691.9

    • Received：28 November 2023，

      Revised：30 January 2024，

      Published：25 June 2024

    移动端阅览

  • CHEN Xijiang,SUN Xi,ZHAO Bufan,et al.Part segmentation method of point cloud considering optimal allocation and optimal mask[J].Optics and Precision Engineering,2024,32(12):1941-1953. DOI： 10.37188/OPE.20243212.1941.

  •  
  •  

0

Views

73

下载量

0

CSCD

Alert me when the article has been cited
提交
Tools
Download
Export Citation
Share
Add to favorites
Add to my album

Related Articles

Rotating point cloud segmentation and reverse reconstruction based on computed tomography images
Ground point cloud segmentation based on local threshold adaptive method
Small sample data augmentation and abundances inversion of minerals hyperspectral
Saliency maps for point cloud recognition models
Bone scintigraphic classification method based on ACGAN and transfer learning

Related Author

WANG Junyao
QIN Qian
ZOU Yongning
WEI Huihong
ZHANG Peixiang
WANG Qi
GAO Renjing
XIA Yang

Related Institution

College of Optoelectronic Engineering， Chongqing University
BYD Auto Industry Company Limited
Ningbo Institute of Dalian University of Technology
State Key Laboratory of Structural Analysis， Optimization and CAE Software for Industrial Equipment， School of Automotive Engineering， Dalian University of Technology
National Key Laboratory of Remote Sensing Information and Imagery Analyzing Technology， Beijing Research Institute of Uranium Geology
0