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Journal of Library and Information Science in Agriculture ›› 2021, Vol. 33 ›› Issue (4): 58-67.doi: 10.13998/j.cnki.issn1002-1248.20-0670

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• Research paper • Previous Articles     Next Articles

The Intelligent Diagnosis Model of Fruit Tree Disease Based on ResNet-50

JIN Ying1, YE Sa2,*, LI Honglei1   

  1. 1. School of Government Management, Liaoning Normal University, Dalian 116029;
    2. Institute of Agricultural Information, Chinese Academy of Agricultural Sciences, Beijing 100081
  • Received:2020-07-28 Online:2021-04-05 Published:2021-04-30

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Abstract: [Purpose/Significance] Fruit tree diseases endanger the safety of agricultural production, and the use of artificial intelligence technologies to help fruit growers identify fruit tree diseases in a timely and accurate manner is of great significance to ensure safe agricultural production. [Method/Process] Using 10 000 fruit tree leaf diseased spots image data sets, through image enhancement methods such as rotation, pollution, noise enhancement, and cutting to improve the diversity of sample images; using the ResNet-50 deep convolutional network model to perform machine learning to obtain the fruit tree diseases identification model, and develop application software based on this model to provide online diagnostic services. [Results/Conclusions] The experimental results show that the average recognition rate of the four fruit tree diseases reached 92.9%, which has a better diagnostic effect compared with related research results.

Key words: ResNet-50, image recognition, fruit tree disease, intelligent diagnosis

CLC Number: 

  • G249.2
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