Soybean disease detection system based on convolutional neural network under Caffe framework

doi:10.3969/j.issn.1004-1524.2019.07.19

›› 2019, Vol. 31 ›› Issue (7): 1177-1183.DOI: 10.3969/j.issn.1004-1524.2019.07.19

• Biosystems Engineering • Previous Articles Next Articles

Soybean disease detection system based on convolutional neural network under Caffe framework

JIANG Fengqian^1,2, LI Yang^1,2,*, YU Dawei^1,2, SUN Min^1,2, ZHANG Enbao^1,2

1. School of Information & Computer Science, Anhui Agriculture University, Hefei 230036, China;
2.Key Laboratory of Technology Integration and Application in Agricultural Internet of Things, Ministry of Agriculture and Rural Affairs, Hefei 230036, China

Received:2018-12-29 Online:2019-07-25 Published:2019-08-07

Abstract

Abstract: The diseases such as leaf spot, mosaic, downy mildew and gray spot of soybean were analysed, and then a soybean disease identification system based on convolutional neural network was proposed. The training set of the neural network model was obtained by the pretreatments including binarization of disease images and extraction of target regions, moreover, the accuracy of the model was improved, and the model and related parameters were simulated under the Caffe framework. Furthermore, in order to improve the ease and reliability of the system in use, the human-computer interaction interface was designed by using Qt software. The data visualization was further realized.

Key words: soybean diseases, convolution neural network, Caffe, interactive interface, data visualization

CLC Number:

JIANG Fengqian, LI Yang, YU Dawei, SUN Min, ZHANG Enbao. Soybean disease detection system based on convolutional neural network under Caffe framework[J]. , 2019, 31(7): 1177-1183.

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Soybean disease detection system based on convolutional neural network under Caffe framework

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