基于深度学习、考虑最优分配和最优掩膜的点云部分分割方法

IF 1.2 4区地球科学 Q3 ENGINEERING, CIVIL

Survey Review Pub Date : 2024-03-05 DOI:10.1080/00396265.2024.2323289

Xijiang Chen, Xi Sun, Bufan Zhao, Dongmei Tan, Chong Wu

引用次数: 0

摘要

为了增强网络的泛化能力并提高部件分割的精度，一种考虑了最优分配的点云部件分割方法被提出来。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Part segmentation method of point cloud considering optimal allocation and optimal mask based on deep learning

In order to enhance the generalization ability of the network and improve the precision of the part segmentation, a point cloud part segmentation method which takes into account the optimal allocat...

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Survey Review 地学-地球科学综合

CiteScore

3.50

自引率

6.20%

发文量

审稿时长

6 months

期刊介绍： Survey Review is an international journal that has been published since 1931, until recently under the auspices of the Commonwealth Association of Surveying and Land Economy (CASLE). The journal is now published for Survey Review Ltd and brings together research, theory and practice of positioning and measurement, engineering surveying, cadastre and land management, and spatial information management. All papers are peer reviewed and are drawn from an international community, including government, private industry and academia. Survey Review is invaluable to practitioners, academics, researchers and students who are anxious to maintain their currency of knowledge in a rapidly developing field.