基于卷积神经网络的面向对象露天采场提取
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胡乃勋,陈涛,甄娜,牛瑞卿
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Object-oriented Open Pit Extraction based on Convolutional Neural Network
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Naixun Hu,Tao Chen,Na Zhen,Ruiqing Niu
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表3 CNN/SVM分类结果精度评价混淆矩阵
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Table 3 Confusion matrix for accuracy evaluation of CNN/SVM classification result
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| 露天采场 | 道路 | 水体 | 植被 | 建筑物 | 矿山堆积 | 裸土 | 小计 |
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露天采场 | 1 948/1 822 | 21/24 | 5/38 | 0/0 | 47/96 | 85/103 | 1/1 | 2 107/2 084 | 道路 | 25/93 | 911/855 | 1/0 | 0/2 | 30/90 | 8/20 | 2/5 | 977/1 065 | 水体 | 15/4 | 0/0 | 117/78 | 0/0 | 0/1 | 1/0 | 0/0 | 133 | 植被 | 3/4 | 0/2 | 0/2 | 991/990 | 3/19 | 0/4 | 4/11 | 1 001/1 032 | 建筑 | 42/115 | 16/82 | 0/5 | 2/1 | 1 873/1 776 | 4/29 | 2/1 | 1 939/2 009 | 矿山堆积 | 149/156 | 36/21 | 0/1 | 0/2 | 44/16 | 489/436 | 12/27 | 730/659 | 裸土 | 17/5 | 3/3 | 1/0 | 5/3 | 3/2 | 9/4 | 393/369 | 431/386 | 小计 | 2 199/2 199 | 987/987 | 124/124 | 998/998 | 2 000/2 000 | 596/596 | 414/414 | 7 318/7 318 |
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