Jianghe Xing, Zhenwei Li, Jun Li, Shouhang Du, Wei Li, Chengye Zhang
{"title":"基于对象的分析与卷积神经网络多层次融合的分类框架:矿区土地利用分类案例研究","authors":"Jianghe Xing, Zhenwei Li, Jun Li, Shouhang Du, Wei Li, Chengye Zhang","doi":"10.1080/10095020.2024.2336594","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":48531,"journal":{"name":"Geo-spatial Information Science","volume":null,"pages":null},"PeriodicalIF":4.4000,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A classification framework with multi-level fusion of object-based analysis and convolutional neural network: a case study for land use classification in mining areas\",\"authors\":\"Jianghe Xing, Zhenwei Li, Jun Li, Shouhang Du, Wei Li, Chengye Zhang\",\"doi\":\"10.1080/10095020.2024.2336594\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\",\"PeriodicalId\":48531,\"journal\":{\"name\":\"Geo-spatial Information Science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.4000,\"publicationDate\":\"2024-04-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Geo-spatial Information Science\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1080/10095020.2024.2336594\",\"RegionNum\":1,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"REMOTE SENSING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geo-spatial Information Science","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1080/10095020.2024.2336594","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"REMOTE SENSING","Score":null,"Total":0}
A classification framework with multi-level fusion of object-based analysis and convolutional neural network: a case study for land use classification in mining areas
期刊介绍:
Geo-spatial Information Science was founded in 1998 by Wuhan University, and is now published in partnership with Taylor & Francis. The journal publishes high quality research on the application and development of surveying and mapping technology, including photogrammetry, remote sensing, geographical information systems, cartography, engineering surveying, GPS, geodesy, geomatics, geophysics, and other related fields. The journal particularly encourages papers on innovative applications and theories in the fields above, or of an interdisciplinary nature. In addition to serving as a source reference and archive of advancements in these disciplines, Geo-spatial Information Science aims to provide a platform for communication between researchers and professionals concerned with the topics above. The editorial committee of the journal consists of 21 professors and research scientists from different regions and countries, such as America, Germany, Switzerland, Austria, Hong Kong and China.