ISSN 2394-5125
 


    Deep Learning Using Research on Recognition Model of Crop Diseases and Insect Pests in Harsh Environments (2020)


    Patlannagari Hasitha Reddy, Soujanya Satla
    JCR. 2020: 3887-3896

    Abstract

    Agricultural diseases and insect pests are one of the most important factors that seriously threaten agricultural production. Early detection and identification of pests can effectively reduce the economic losses caused by pests. In this paper, convolution neural network is used to automatically identify crop diseases. In this paper, the CNN model is used for training. After the combined convolution operation is completed, it is activated by the connection into the ReLu function. The experimental results show that the overall recognition accuracy is 86.1% in this model, which verifies the effectiveness. The results show that the system can accurately identify crop diseases and give the corresponding guidance. Finally, the simulations revealed that the proposed ResNet CNN resulted in superior performance as compared to NB, SVM and RF.

    Description

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    Volume & Issue

    Volume 7 Issue-8

    Keywords