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《Chinese Journal of Rice Science》 2019-01
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Rhizocotonia Solani Recognition Algorithm Based on Convolutional Neural Network

LIU Tingting;WANG Ting;HU Lin;Key Laboratory of Agricultural Big Data,Ministry of Agriculture/Agricultural Information Institute of Chinese Academy of Agricultural Sciences;  
【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.
【Fund】: 中国农业科学院基本科研业务费项目(Y2017LM07);中国农业科学院农业信息研究所基本科研业务费项目(JBYW-AII-2017-32)
【CateGory Index】: S435.111.42;TP391.41
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