中国水稻科学 ›› 2019, Vol. 33 ›› Issue (1): 90-94.DOI: 10.16819/j.1001-7216.2019.8051
• 研究简报 • 上一篇
收稿日期:
2018-04-23
修回日期:
2018-10-16
出版日期:
2019-01-10
发布日期:
2019-01-10
通讯作者:
胡林
Tingting LIU, Ting WANG, Lin HU*()
Received:
2018-04-23
Revised:
2018-10-16
Online:
2019-01-10
Published:
2019-01-10
Contact:
Lin HU
摘要:
【目的】水稻纹枯病是影响水稻生产的三大病害之一。研究卷积神经网络对水稻纹枯病的自动识别,弥补人工识别的不足,对预防和准确识别水稻蚊枯病类型有着重要意义。【方法】以卷积神经网络进行水稻纹枯病识别,并与基于支持向量机的识别方法进行对比。【结果】卷积神经网络识别率达到97%,优于支持向量机的95%。【结论】卷积神经网络运用于水稻纹枯病识别是可行的,弥补了人工识别的不足。此算法训练的模型有着较好的识别性能。
中图分类号:
刘婷婷, 王婷, 胡林. 基于卷积神经网络的水稻纹枯病图像识别[J]. 中国水稻科学, 2019, 33(1): 90-94.
Tingting LIU, Ting WANG, Lin HU. Rhizocotonia Solani Recognition Algorithm Based on Convolutional Neural Network[J]. Chinese Journal OF Rice Science, 2019, 33(1): 90-94.
样本正确识别率 Correct recognition rate of samples | 第一次 First | 第二次 Second | 第三次 Third | 第四次 Fourth | 第五次 Fifth |
---|---|---|---|---|---|
卷积神经网络CNN | 100.0 | 95.0 | 92.5 | 97.5 | 100.0 |
支持向量机SVM | 97.5 | 92.5 | 90.0 | 95.0 | 100.0 |
表1 识别算法结果对照
Table 1 Comparison of recognition algorithm results. %
样本正确识别率 Correct recognition rate of samples | 第一次 First | 第二次 Second | 第三次 Third | 第四次 Fourth | 第五次 Fifth |
---|---|---|---|---|---|
卷积神经网络CNN | 100.0 | 95.0 | 92.5 | 97.5 | 100.0 |
支持向量机SVM | 97.5 | 92.5 | 90.0 | 95.0 | 100.0 |
识别算法 Recognition algorithm | 观测数 Observation number | 求和 Sum | 平均 Average | 方差 Variance |
---|---|---|---|---|
行1:卷积神经网络Row1:CNN | 5 | 4.850 | 0.9700 | 0.0011 |
行2:支持向量机Row2:SVM | 5 | 4.750 | 0.9500 | 0.0016 |
列1:第一次Column1:First | 2 | 1.975 | 0.9875 | 0.0003 |
列2:第二次Column2:Second | 2 | 1.875 | 0.9375 | 0.0003 |
列3:第三次Column3:Third | 2 | 1.825 | 0.9125 | 0.0003 |
列4:第四次Column4:Fourth | 2 | 1.925 | 0.9625 | 0.0003 |
列5:第五次Column5:Fifth | 2 | 2.000 | 1.0000 | 0.0003 |
表2 识别算法结果方差分析
Table 2 Comparison of recognition algorithm results analysis of variance.
识别算法 Recognition algorithm | 观测数 Observation number | 求和 Sum | 平均 Average | 方差 Variance |
---|---|---|---|---|
行1:卷积神经网络Row1:CNN | 5 | 4.850 | 0.9700 | 0.0011 |
行2:支持向量机Row2:SVM | 5 | 4.750 | 0.9500 | 0.0016 |
列1:第一次Column1:First | 2 | 1.975 | 0.9875 | 0.0003 |
列2:第二次Column2:Second | 2 | 1.875 | 0.9375 | 0.0003 |
列3:第三次Column3:Third | 2 | 1.825 | 0.9125 | 0.0003 |
列4:第四次Column4:Fourth | 2 | 1.925 | 0.9625 | 0.0003 |
列5:第五次Column5:Fifth | 2 | 2.000 | 1.0000 | 0.0003 |
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