Identification of Rice Leaf Disease Using Improved ShuffleNet V2  

作　　者：Yang Zhou Chunjiao Fu Yuting Zhai Jian Li Ziqi Jin Yanlei Xu 

机构地区：[1]College of Information and Technology,Jilin Agricultural University,Changchun,130118,China

出　　处：《Computers, Materials & Continua》2023年第5期4501-4517,共17页计算机、材料和连续体（英文）

基　　金：This work is supported in part by the Ji Lin provincial science and technology department international science and technology cooperation project under Grant 20200801014GH;the Changchun City Science and Technology Bureau key science and technology research projects under Grant 21ZGN28.

摘　　要：Accurate identification of rice diseases is crucial for controlling diseases and improving rice yield.To improve the classification accuracy of rice diseases,this paper proposed a classification and identification method based on an improved ShuffleNet V2(GE-ShuffleNet)model.Firstly,the Ghost module is used to replace the 1×1 convolution in the two basic unit modules of ShuffleNet V2,and the unimportant 1×1 convolution is deleted from the two basic unit modules of ShuffleNet V2.The Hardswish activation function is applied to replace the ReLU activation function to improve the identification accuracy of the model.Secondly,an effective channel attention(ECA)module is added to the network to avoid dimension reduction,and the correlation between channels is effectively extracted through 1D convolution.Besides,L2 regularization is introduced to fine-tune the training parameters during training to prevent overfitting.Finally,the considerable experimental and numerical results proved the advantages of our proposed model in terms of model size,floating-point operation per second(FLOPs),and parameters(Params).Especially in the case of smaller model size(5.879 M),the identification accuracy of GE-ShuffleNet(96.6%)is higher than that of ShuffleNet V2(94.4%),MobileNet V2(93.7%),AlexNet(79.1%),Swim Transformer(88.1%),EfficientNet V2(89.7%),VGG16(81.9%),GhostNet(89.3%)and ResNet50(92.5%).

关 键 词：Deep learning convolution neural network rice diseases lightweight network 

分 类 号：S432[农业科学—植物病理学]