Xinjiang Agricultural Sciences ›› 2024, Vol. 61 ›› Issue (10): 2547-2556.DOI: 10.6048/j.issn.1001-4330.2024.10.022
• Plant Protection · Soil Fertilizer · Water Saving Irrigation · Agricultural Equipment Engineering and Mechanization · Prataculture • Previous Articles Next Articles
QIN Yekangyang(), LI Jiaxin, JIN Guili(
), LIU Wenhao, MA Jian, LI Wenxiong, CHEN Mentian
Received:
2024-03-11
Online:
2024-10-20
Published:
2024-11-07
Correspondence author:
JIN Guili
Supported by:
秦叶康阳(), 李嘉欣, 靳瑰丽(
), 刘文昊, 马建, 李文雄, 陈梦甜
通讯作者:
靳瑰丽
作者简介:
秦叶康阳(2001-),男,江苏沛县人,本科,研究方向为草业科学,(E-mail)2095782457@qq.com
基金资助:
CLC Number:
QIN Yekangyang, LI Jiaxin, JIN Guili, LIU Wenhao, MA Jian, LI Wenxiong, CHEN Mentian. Identification of main plants in desert grassland Seriphidium transiliense based on UAV remote sensing and CNN ResNet 18[J]. Xinjiang Agricultural Sciences, 2024, 61(10): 2547-2556.
秦叶康阳, 李嘉欣, 靳瑰丽, 刘文昊, 马建, 李文雄, 陈梦甜. 基于UAV和CNN ResNet 18参数调节的伊犁绢蒿荒漠草地植物识别性能分析[J]. 新疆农业科学, 2024, 61(10): 2547-2556.
超参数调节 Hyper- parameters adjustment | 序号 Number | 训练轮数 Epoch | 批量规模 Batch sizes | 学习率 Learning rates |
---|---|---|---|---|
训练轮数调节 Epoch adjustment | 1 | 40 | 8 | 0.001 |
2 | 80 | 8 | 0.001 | |
批量规模调节 Batch size adjustment | 3 | 40 | 8 | 0.001 |
4 | 40 | 16 | 0.001 | |
5 | 40 | 32 | 0.001 | |
6 | 40 | 64 | 0.001 | |
学习率调节 Learning rate adjustment | 7 | 40 | 8 | 0.01 |
8 | 40 | 8 | 0.005 | |
9 | 40 | 8 | 0.001 | |
10 | 40 | 8 | 0.000 5 | |
11 | 40 | 8 | 0.000 1 |
Tab.1 ResNet 18 Model Parameter Design Table
超参数调节 Hyper- parameters adjustment | 序号 Number | 训练轮数 Epoch | 批量规模 Batch sizes | 学习率 Learning rates |
---|---|---|---|---|
训练轮数调节 Epoch adjustment | 1 | 40 | 8 | 0.001 |
2 | 80 | 8 | 0.001 | |
批量规模调节 Batch size adjustment | 3 | 40 | 8 | 0.001 |
4 | 40 | 16 | 0.001 | |
5 | 40 | 32 | 0.001 | |
6 | 40 | 64 | 0.001 | |
学习率调节 Learning rate adjustment | 7 | 40 | 8 | 0.01 |
8 | 40 | 8 | 0.005 | |
9 | 40 | 8 | 0.001 | |
10 | 40 | 8 | 0.000 5 | |
11 | 40 | 8 | 0.000 1 |
序号 Number | 训练 轮数 Epoch | 批量 规模 Batch sizes | 学习率 Learning rates | 识别精度 Identification accuracy(%) | |||
---|---|---|---|---|---|---|---|
伊犁绢蒿 Seriphidium transiliense | 角果藜 Ceratocarpus arenarius | 裸地 Bare land | 总体 Overall accuracy | ||||
1 | 40 | 8 | 0.001 | 84.21 | 81.15 | 86.41 | 83.65 |
2 | 80 | 8 | 0.001 | 80.21 | 76.18 | 91.48 | 82.51 |
Tab.2 Changes of identification accuracy of different training rounds
序号 Number | 训练 轮数 Epoch | 批量 规模 Batch sizes | 学习率 Learning rates | 识别精度 Identification accuracy(%) | |||
---|---|---|---|---|---|---|---|
伊犁绢蒿 Seriphidium transiliense | 角果藜 Ceratocarpus arenarius | 裸地 Bare land | 总体 Overall accuracy | ||||
1 | 40 | 8 | 0.001 | 84.21 | 81.15 | 86.41 | 83.65 |
2 | 80 | 8 | 0.001 | 80.21 | 76.18 | 91.48 | 82.51 |
序号 Number | 训练 轮数 Epoch | 批量 规模 Batch sizes | 学习率 Learning rates | 识别精度 Identification accuracy(%) | |||
---|---|---|---|---|---|---|---|
伊犁绢蒿 Seriphidium transiliense | 角果藜 Ceratocarpus arenarius | 裸地 Bare land | 总体 Overall accuracy | ||||
1 | 40 | 8 | 0.001 | 84.21 | 81.15 | 86.41 | 83.65 |
2 | 40 | 16 | 0.001 | 90.90 | 81.17 | 82.40 | 83.90 |
3 | 40 | 32 | 0.001 | 88.88 | 81.48 | 84.27 | 84.19 |
4 | 40 | 64 | 0.001 | 76.51 | 89.10 | 81.95 | 83.22 |
Tab.3 Changes of identification accuracy of different batch sizes
序号 Number | 训练 轮数 Epoch | 批量 规模 Batch sizes | 学习率 Learning rates | 识别精度 Identification accuracy(%) | |||
---|---|---|---|---|---|---|---|
伊犁绢蒿 Seriphidium transiliense | 角果藜 Ceratocarpus arenarius | 裸地 Bare land | 总体 Overall accuracy | ||||
1 | 40 | 8 | 0.001 | 84.21 | 81.15 | 86.41 | 83.65 |
2 | 40 | 16 | 0.001 | 90.90 | 81.17 | 82.40 | 83.90 |
3 | 40 | 32 | 0.001 | 88.88 | 81.48 | 84.27 | 84.19 |
4 | 40 | 64 | 0.001 | 76.51 | 89.10 | 81.95 | 83.22 |
序号 Number | 训练 轮数 Epoch | 批量 规模 Batch size | 学习率 Learning rates | 识别精度 Identification accuracy(%) | |||
---|---|---|---|---|---|---|---|
伊犁绢蒿 Seriphidium transiliense | 角果藜 Ceratocarpus arenarius | 裸地Bare land | 总体 Overall accuracy | ||||
1 | 40 | 8 | 0.01 | 87.94 | 74.31 | 84.65 | 81.29 |
2 | 40 | 8 | 0.005 | 86.42 | 78.85 | 83.85 | 82.40 |
3 | 40 | 8 | 0.001 | 84.21 | 81.15 | 86.41 | 83.65 |
4 | 40 | 8 | 0.000 5 | 89.66 | 79.33 | 86.27 | 84.26 |
5 | 40 | 8 | 0.000 1 | 81.37 | 86.12 | 87.10 | 85.12 |
Tab.4 Changes of identification accuracy of different learning rates
序号 Number | 训练 轮数 Epoch | 批量 规模 Batch size | 学习率 Learning rates | 识别精度 Identification accuracy(%) | |||
---|---|---|---|---|---|---|---|
伊犁绢蒿 Seriphidium transiliense | 角果藜 Ceratocarpus arenarius | 裸地Bare land | 总体 Overall accuracy | ||||
1 | 40 | 8 | 0.01 | 87.94 | 74.31 | 84.65 | 81.29 |
2 | 40 | 8 | 0.005 | 86.42 | 78.85 | 83.85 | 82.40 |
3 | 40 | 8 | 0.001 | 84.21 | 81.15 | 86.41 | 83.65 |
4 | 40 | 8 | 0.000 5 | 89.66 | 79.33 | 86.27 | 84.26 |
5 | 40 | 8 | 0.000 1 | 81.37 | 86.12 | 87.10 | 85.12 |
评价指标 Evaluating indicator | 学习率Learning rates | ||||
---|---|---|---|---|---|
0.01 | 0.005 | 0.001 | 0.0005 | 0.0001 | |
总体分类精度 Overall accuracy(%) | 81.29 | 82.40 | 83.65 | 84.26 | 85.12 |
收敛速度 Convergence rate | 较快 | 较快 | 较快 | 快 | 较快 |
收敛效果 Convergence effect | 好 | 好 | 好 | 好 | 好 |
拟合效果 Fitting results | 较好 | 较好 | 较好 | 好 | 好 |
运行时间 Running time | 283分53秒 | 355分59秒 | 217分32秒 | 204分39秒 | 226分32秒 |
Tab.5 Comprehensive evaluation of model performance with different learning rates
评价指标 Evaluating indicator | 学习率Learning rates | ||||
---|---|---|---|---|---|
0.01 | 0.005 | 0.001 | 0.0005 | 0.0001 | |
总体分类精度 Overall accuracy(%) | 81.29 | 82.40 | 83.65 | 84.26 | 85.12 |
收敛速度 Convergence rate | 较快 | 较快 | 较快 | 快 | 较快 |
收敛效果 Convergence effect | 好 | 好 | 好 | 好 | 好 |
拟合效果 Fitting results | 较好 | 较好 | 较好 | 好 | 好 |
运行时间 Running time | 283分53秒 | 355分59秒 | 217分32秒 | 204分39秒 | 226分32秒 |
Fig. 8 Visualization of model identification results under different learning rates Notes:The serial numbers Ⅰ~Ⅴ indicate that the model learning rate is set to 0.01, 0.005, 0.001, 0.000 5, 0.000 1
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