Scientia Silvae Sinicae ›› 2020, Vol. 56 ›› Issue (10): 121-128.doi: 10.11707/j.1001-7488.20201013
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Guangqun Zhang1,Yingjie Li2,Hangjun Wang2,*,Houkui Zhou1
Received:
2018-05-28
Online:
2020-10-25
Published:
2020-11-26
Contact:
Hangjun Wang
CLC Number:
Guangqun Zhang,Yingjie Li,Hangjun Wang,Houkui Zhou. Forest Image Classification Based on Fine-Tuning CaffeNet[J]. Scientia Silvae Sinicae, 2020, 56(10): 121-128.
Table 1
Network structure and its parameters"
层号Layer No. | 层名称 Layer name | 具体配置 Particular configuration |
0 | Input | 240×240×3,RGB |
1 | conv1 | kernel_size=11, stride=4, pad=0, num_output=96 |
2 | pool1 | kernel_size=2, stride=2, pad=0 |
3 | conv2 | kernel_size=5, stride=1, pad=2, num_output=256 |
4 | pool2 | kernel_size=3, stride=2, pad=0 |
5 | conv3 | kernel_size=3, stride=1, pad=1, num_output=384 |
6 | conv4 | kernel_size=3, stride=1, pad=1, num_output=384 |
7 | conv5 | kernel_size=3, stride=1, pad=1, num_output=256 |
8 | pool5 | kernel_size=3, stride=2, pad=0 |
9 | fc6 | num_output=4 096 |
10 | fc7 | num_output=4 096 |
11 | fc8 | num_output=4 |
13 | loss | SoftmaxWithLoss, loss |
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