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预训练 CNN 在温带毁林检测中的适用性

IF 3.7 4区 地球科学 Q2 REMOTE SENSING
European Journal of Remote Sensing Pub Date : 2024-06-18 DOI:10.1080/22797254.2024.2367221
Lucian Coţolan, Darie Moldovan
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引用次数: 0

摘要

技术进步为准确识别毁林区域和制定有效的数据收集策略提供了新的可能性。我们的论文提出了一种实用的方法 ...
本文章由计算机程序翻译，如有差异，请以英文原文为准。
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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 ...
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来源期刊
European Journal of Remote Sensing
European Journal of Remote Sensing REMOTE SENSING-
CiteScore
7.00
自引率
2.50%
发文量
51
审稿时长
>12 weeks
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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