Journal of Agricultural Science and Technology ›› 2023, Vol. 25 ›› Issue (6): 97-106.DOI: 10.13304/j.nykjdb.2022.0633
• INTELLIGENT AGRICULTURE & AGRICULTURAL MACHINERY • Previous Articles Next Articles
Wei ZHAO(), Rui MA, Jia WANG, Hongjie GUO, Jinpu XU(
)
Received:
2022-07-29
Accepted:
2022-10-24
Online:
2023-06-01
Published:
2023-07-28
Contact:
Jinpu XU
通讯作者:
许金普
作者简介:
赵威 E-mail:1981960020@qq.com;
基金资助:
CLC Number:
Wei ZHAO, Rui MA, Jia WANG, Hongjie GUO, Jinpu XU. Classification and Identification of Corn Varieties Based on Ear Image[J]. Journal of Agricultural Science and Technology, 2023, 25(6): 97-106.
赵威, 马睿, 王佳, 郭宏杰, 许金普. 基于果穗图像的玉米品种分类识别[J]. 中国农业科技导报, 2023, 25(6): 97-106.
类别 Category | 训练集 Training set | 验证集 Validation set | 测试集 Test set | 总计 Total | 训练集增强后总计 Training set enhanced total |
---|---|---|---|---|---|
锦玉118 Jinyu 118 | 140 | 40 | 20 | 200 | 980 |
科诺58 Kenuo 58 | 140 | 40 | 20 | 200 | 980 |
立原296 Liyuan 296 | 140 | 40 | 20 | 200 | 980 |
铁研630 Tieyan 630 | 140 | 40 | 20 | 200 | 980 |
荟玉18 Huiyu 18 | 140 | 40 | 20 | 200 | 980 |
Table 1 Corn ear dataset
类别 Category | 训练集 Training set | 验证集 Validation set | 测试集 Test set | 总计 Total | 训练集增强后总计 Training set enhanced total |
---|---|---|---|---|---|
锦玉118 Jinyu 118 | 140 | 40 | 20 | 200 | 980 |
科诺58 Kenuo 58 | 140 | 40 | 20 | 200 | 980 |
立原296 Liyuan 296 | 140 | 40 | 20 | 200 | 980 |
铁研630 Tieyan 630 | 140 | 40 | 20 | 200 | 980 |
荟玉18 Huiyu 18 | 140 | 40 | 20 | 200 | 980 |
模型Model | NASNet-mobile | Xception | ResNet50V2 | MobileNetV2 | DenseNet121 | VGG16 |
---|---|---|---|---|---|---|
测试准确率 Test accuracy | 0.90 | 0.88 | 0.80 | 0.88 | 0.89 | 0.83 |
Table 2 Baseline test accuracy of network models
模型Model | NASNet-mobile | Xception | ResNet50V2 | MobileNetV2 | DenseNet121 | VGG16 |
---|---|---|---|---|---|---|
测试准确率 Test accuracy | 0.90 | 0.88 | 0.80 | 0.88 | 0.89 | 0.83 |
指标 Index | 基线 Benchmark | Batch_size:32 | Batch_size:64 | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
T=1 D=256 | T=2 D=256 | T=3 D=256 | T=1 D=512 | T=2 D=512 | T=3 D=512 | T=1 D=256 | T=2 D=256 | T=3 D=256 | T=1 D=512 | T=2 D=512 | T=3 D=512 | ||
精准率Precision | 0.908 7 | 0.923 1 | 0.956 1 | 0.907 9 | 0.916 8 | 0.909 4 | 0.928 2 | 0.912 5 | 0.920 2 | 0.925 9 | 0.918 5 | 0.874 1 | 0.923 0 |
召回率Recall | 0.900 0 | 0.920 0 | 0.950 0 | 0.890 0 | 0.890 0 | 0.860 0 | 0.920 0 | 0.910 0 | 0.910 0 | 0.910 0 | 0.880 0 | 0.830 0 | 0.920 0 |
调和平均值F1-score | 0.901 4 | 0.921 5 | 0.950 5 | 0.893 4 | 0.892 1 | 0.863 6 | 0.920 5 | 0.910 6 | 0.909 7 | 0.912 1 | 0.883 4 | 0.834 8 | 0.920 4 |
准确率Accuracy | 0.900 0 | 0.920 0 | 0.950 0 | 0.890 0 | 0.890 0 | 0.860 0 | 0.920 0 | 0.910 0 | 0.910 0 | 0.910 0 | 0.880 0 | 0.830 0 | 0.920 0 |
Table 3 Model performance evaluation under different full connection layer modules
指标 Index | 基线 Benchmark | Batch_size:32 | Batch_size:64 | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
T=1 D=256 | T=2 D=256 | T=3 D=256 | T=1 D=512 | T=2 D=512 | T=3 D=512 | T=1 D=256 | T=2 D=256 | T=3 D=256 | T=1 D=512 | T=2 D=512 | T=3 D=512 | ||
精准率Precision | 0.908 7 | 0.923 1 | 0.956 1 | 0.907 9 | 0.916 8 | 0.909 4 | 0.928 2 | 0.912 5 | 0.920 2 | 0.925 9 | 0.918 5 | 0.874 1 | 0.923 0 |
召回率Recall | 0.900 0 | 0.920 0 | 0.950 0 | 0.890 0 | 0.890 0 | 0.860 0 | 0.920 0 | 0.910 0 | 0.910 0 | 0.910 0 | 0.880 0 | 0.830 0 | 0.920 0 |
调和平均值F1-score | 0.901 4 | 0.921 5 | 0.950 5 | 0.893 4 | 0.892 1 | 0.863 6 | 0.920 5 | 0.910 6 | 0.909 7 | 0.912 1 | 0.883 4 | 0.834 8 | 0.920 4 |
准确率Accuracy | 0.900 0 | 0.920 0 | 0.950 0 | 0.890 0 | 0.890 0 | 0.860 0 | 0.920 0 | 0.910 0 | 0.910 0 | 0.910 0 | 0.880 0 | 0.830 0 | 0.920 0 |
指标index | 荟玉18 Huiyu 18 | 锦玉118 Jinyu 118 | 科诺58 Kenuo 58 | 立原296 Liyuan 296 | 铁研630 Tieyan 630 | 平均Mean |
---|---|---|---|---|---|---|
精准率Precision | 0.947 3 | 0.833 3 | 1.000 0 | 1.000 0 | 1.000 0 | 0.956 1 |
召回率Recall | 0.900 0 | 1.000 0 | 0.900 0 | 0.950 0 | 1.000 0 | 0.950 0 |
调和平均值F1-score | 0.923 0 | 0.909 0 | 0.947 3 | 0.974 3 | 1.000 0 | 0.950 7 |
准确率Accuracy | 0.900 0 | 1.000 0 | 0.900 0 | 0.950 0 | 1.000 0 | 0.950 0 |
Table 4 Evaluation indexes of ear test results of different varieties of maize under NASNet-mobile-maize model
指标index | 荟玉18 Huiyu 18 | 锦玉118 Jinyu 118 | 科诺58 Kenuo 58 | 立原296 Liyuan 296 | 铁研630 Tieyan 630 | 平均Mean |
---|---|---|---|---|---|---|
精准率Precision | 0.947 3 | 0.833 3 | 1.000 0 | 1.000 0 | 1.000 0 | 0.956 1 |
召回率Recall | 0.900 0 | 1.000 0 | 0.900 0 | 0.950 0 | 1.000 0 | 0.950 0 |
调和平均值F1-score | 0.923 0 | 0.909 0 | 0.947 3 | 0.974 3 | 1.000 0 | 0.950 7 |
准确率Accuracy | 0.900 0 | 1.000 0 | 0.900 0 | 0.950 0 | 1.000 0 | 0.950 0 |
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