{"title":"预训练 CNN 在温带毁林检测中的适用性","authors":"Lucian Coţolan, Darie Moldovan","doi":"10.1080/22797254.2024.2367221","DOIUrl":null,"url":null,"abstract":"Technological advancements have opened up new possibilities for accurately identifying deforested areas and developing effective data collection strategies. Our paper proposes a practical approach ...","PeriodicalId":49077,"journal":{"name":"European Journal of Remote Sensing","volume":"159 1","pages":""},"PeriodicalIF":3.7000,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Applicability of pre-trained CNNs in temperate deforestation detection\",\"authors\":\"Lucian Coţolan, Darie Moldovan\",\"doi\":\"10.1080/22797254.2024.2367221\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Technological advancements have opened up new possibilities for accurately identifying deforested areas and developing effective data collection strategies. Our paper proposes a practical approach ...\",\"PeriodicalId\":49077,\"journal\":{\"name\":\"European Journal of Remote Sensing\",\"volume\":\"159 1\",\"pages\":\"\"},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2024-06-18\",\"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/10.1080/22797254.2024.2367221\",\"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/10.1080/22797254.2024.2367221","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}
Applicability of pre-trained CNNs in temperate deforestation detection
Technological advancements have opened up new possibilities for accurately identifying deforested areas and developing effective data collection strategies. Our paper proposes a practical approach ...
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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