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VGG-19 Net (with 16 convolutional layers and 3 full connect layers) has more deep structure than other CNN models, which can provide more semantic information.
The new structure, which Intel calls BBUL, for bumpless buildup layer, is thinner and lighter because the silicon chip is embedded in the packaging where the top connecting layer used to sit.
BFCL: Before fully connected layer, AFCL: After fully connected layer.
In both cases, D was a single fully connected layer.
After fully connected layer (AFCL) is the second approach.
In addition, one fully connected layer (FL) is used.
AlexNet is composed of five convolutional layers and three fully connected layers, VGG-16 is composed of 13 convolutional layers and three fully connected layers, and GoogLeNet is composed of 21 convolutional layers and one fully connected layer.
Before fully connected layer (BFCL) provides the features to the fully connected layer of the VGG16, as shown in Fig. 5. Filter size is 14 ×14 with 512 kernels.
It is often placed between two convolutional layers or convolutional layer and fully connected layer.
Dropout layer has been included after first fully connected layer to avoid overfitting.
The reconstruction layer is constructed using a fully connected layer and can be denoted as h4.
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