基于卷积神经网络的水稻纹枯病图像识别
收稿日期: 2018-04-23
修回日期: 2018-10-16
网络出版日期: 2019-01-10
Rhizocotonia Solani Recognition Algorithm Based on Convolutional Neural Network
Received date: 2018-04-23
Revised date: 2018-10-16
Online published: 2019-01-10
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 . DOI: 10.16819/j.1001-7216.2019.8051
【Objective】Rice sheath blight is one of the three major diseases in rice production.The convolutional neural network which stands out for automatic identification of rice shealth blight can compensate for the lack of human identification. To solve this problem and prevent diseases deterioration, accurate identification of diseases types is of great significance.【Method】The convolutional neural network method was used to recognize rice sheath blight and compared with the recognition method based on support vector machine.【Result】The convolutional neural network method showed the recognition rate of 97%, better than that of support vector machine(95%).【Conclusion】The application of convolutional neural network to the identification of rice sheath blight is feasible and makes up for the lack of artificial recognition. The model trained by this algorithm has great recognition performance.
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