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The prepared images were applied to AlexNet+TL, GoogleNet+TL, ResNet 18+TL,

The prepared images were applied to AlexNet+TL, GoogleNet+TL, ResNet 18+TL, 6dlKG

The prepared images were applied to AlexNet+TL, GoogleNet+TL, ResNet 18+TL, and AlexNet+SVM. For these operations, transfer learning (TL) was applied to three trained deep learning architectures (AlexNet, GoogleNet, and ResNet 18) to get better parameterization of these architectures. Also, in AlexNet + SVM, to classify test images, features extracted from training images were used to train the model. At this stage, all the legacy network parameters were replaced with our new data (1000 images divided into 10 categories, 80% for the training stage and 20% for the testing stage). Figure 6 shows the stages of using deep learning architectures in AlexNet+TL.

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