{"title":"基于改进型 PointNet++ 网络的电力走廊分类模型","authors":"Li Bo, Liu Siyuan, Wang Fengxiang, Zou Cunyu","doi":"10.1080/10106049.2023.2297556","DOIUrl":null,"url":null,"abstract":"Aiming at the existing deep learning classification model for power corridor point cloud still need to improve the classification efficiency and the robustness of the classification model to meet t...","PeriodicalId":12532,"journal":{"name":"Geocarto International","volume":null,"pages":null},"PeriodicalIF":3.3000,"publicationDate":"2024-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A classification model for power corridors based on the improved PointNet++ network\",\"authors\":\"Li Bo, Liu Siyuan, Wang Fengxiang, Zou Cunyu\",\"doi\":\"10.1080/10106049.2023.2297556\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Aiming at the existing deep learning classification model for power corridor point cloud still need to improve the classification efficiency and the robustness of the classification model to meet t...\",\"PeriodicalId\":12532,\"journal\":{\"name\":\"Geocarto International\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2024-01-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Geocarto International\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1080/10106049.2023.2297556\",\"RegionNum\":4,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geocarto International","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1080/10106049.2023.2297556","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
A classification model for power corridors based on the improved PointNet++ network
Aiming at the existing deep learning classification model for power corridor point cloud still need to improve the classification efficiency and the robustness of the classification model to meet t...
期刊介绍：
Geocarto International is a professional academic journal serving the world-wide scientific and user community in the fields of remote sensing, GIS, geoscience and environmental sciences. The journal is designed: to promote multidisciplinary research in and application of remote sensing and GIS in geosciences and environmental sciences; to enhance international exchange of information on new developments and applications in the field of remote sensing and GIS and related disciplines; to foster interest in and understanding of science and applications on remote sensing and GIS technologies; and to encourage the publication of timely papers and research results on remote sensing and GIS applications in geosciences and environmental sciences from the world-wide science community.
The journal welcomes contributions on the following: precise, illustrated papers on new developments, technologies and applications of remote sensing; research results in remote sensing, GISciences and related disciplines;
Reports on new and innovative applications and projects in these areas; and assessment and evaluation of new remote sensing and GIS equipment, software and hardware.
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