Densenet based model for plant diseases diagnosis

HIGHLIGHTS

• who: Mahmoud Bakr and collaborators from the ETraining The Models In this step, the chosen CNN models were trained using the plant disease identification data set. The fixed low-level network parameters remain intact throughout the training process while the high-level network parameters are adjusted. The network`s high-level parameters are trained using the plant disease image, and the learned model is then used to categorise the , different types of plant leaves. VGG16, Inception, Resnet, and DenseNet, are the chosen CNN. Simonyan and Zisserman of Google DeepMind and Oxford University`s Visual Geometry Group introduced . . .
  

   

  

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