{"title":"强化大规模建筑物提取评估：利用代用数据和建筑物匹配开发两级框架","authors":"Shenglong Chen, Yoshiki Ogawa, Chenbo Zhao, Yoshihide Sekimoto","doi":"10.1080/22797254.2024.2374844","DOIUrl":null,"url":null,"abstract":"Deep learning-based building extraction methods have widespread applications in diverse fields. However, the evaluation of large-scale extraction results remains challenging, due to traditional eva...","PeriodicalId":49077,"journal":{"name":"European Journal of Remote Sensing","volume":"36 1","pages":""},"PeriodicalIF":3.7000,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Enhanced large-scale building extraction evaluation: developing a two-level framework using proxy data and building matching\",\"authors\":\"Shenglong Chen, Yoshiki Ogawa, Chenbo Zhao, Yoshihide Sekimoto\",\"doi\":\"10.1080/22797254.2024.2374844\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Deep learning-based building extraction methods have widespread applications in diverse fields. However, the evaluation of large-scale extraction results remains challenging, due to traditional eva...\",\"PeriodicalId\":49077,\"journal\":{\"name\":\"European Journal of Remote Sensing\",\"volume\":\"36 1\",\"pages\":\"\"},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2024-07-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European Journal of Remote Sensing\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1080/22797254.2024.2374844\",\"RegionNum\":4,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"REMOTE SENSING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Remote Sensing","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1080/22797254.2024.2374844","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"REMOTE SENSING","Score":null,"Total":0}
Enhanced large-scale building extraction evaluation: developing a two-level framework using proxy data and building matching
Deep learning-based building extraction methods have widespread applications in diverse fields. However, the evaluation of large-scale extraction results remains challenging, due to traditional eva...
期刊介绍：
European Journal of Remote Sensing publishes research papers and review articles related to the use of remote sensing technologies. The Journal welcomes submissions on all applications related to the use of active or passive remote sensing to terrestrial, oceanic, and atmospheric environments. The most common thematic areas covered by the Journal include:
-land use/land cover
-geology, earth and geoscience
-agriculture and forestry
-geography and landscape
-ecology and environmental science
-support to land management
-hydrology and water resources
-atmosphere and meteorology
-oceanography
-new sensor systems, missions and software/algorithms
-pre processing/calibration
-classifications
-time series/change analysis
-data integration/merging/fusion
-image processing and analysis
-modelling
European Journal of Remote Sensing is a fully open access journal. This means all submitted articles will, if accepted, be available for anyone to read anywhere, at any time, immediately on publication. There are no charges for submission to this journal.
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