基于深度学习的高分辨率卫星遥感影像围填海检测识别
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于枫世,隋毅,王常颖,初佳兰
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Reclamation Detection and Recognition of High Resolution Satellite Remote Sensing Image based on Deep Learning
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Fengshi Yu,Yi Sui,Changying Wang,Jialan Chu
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表3 测试区域结果比较
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Table 3 Comparison of test area results
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| 时间 | 模型 | 总体分类精度 | F1-score | Kappa | mIoU |
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| 2016年 | SVM | 0.913 6 | 0.723 6 | 0.657 9 | 0.605 0 | | FCN8s | 0.928 4 | 0.839 7 | 0.779 8 | 0.729 2 | | U-Net | 0.957 4 | 0.908 6 | 0.872 8 | 0.834 4 | | Linknet | 0.957 7 | 0.910 0 | 0.874 3 | 0.836 7 | | MCFCN2 | 0.958 1 | 0.915 3 | 0.879 7 | 0.844 8 | | MCFCN2+后处理 | 0.962 1 | 0.924 3 | 0.892 0 | 0.860 1 | 2020年 | SVM | 0.876 0 | 0.684 9 | 0.589 0 | 0.547 5 | | FCN8s | 0.931 7 | 0.844 0 | 0.789 9 | 0.735 8 | | U-Net | 0.955 5 | 0.905 5 | 0.870 4 | 0.829 1 | | Linknet | 0.955 7 | 0.904 0 | 0.869 4 | 0.826 9 | | MCFCN2 | 0.961 2 | 0.914 1 | 0.883 5 | 0.843 7 | | MCFCN2+后处理 | 0.967 3 | 0.928 7 | 0.902 8 | 0.868 2 |
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