There are three typical ways of using pre-trained neural networks. They are listed as follows:
- Reusing the models: Consider an example where we apply a pre-trained neural network and retrieve the image class. Depending on performance requirements, this could be MobileNet, Inception, VGG, ResNet, or any other that is available out there.
- Changing the network structure: Consider an example where we are replacing the last FullyConnected and SoftmaxOutput layers with a different combination. This would be similar to using a CIFAR-10 model with an MNIST dataset. The difference in the implementation is very tiny and updating the last layers would boost the training time.
- Feature extraction: Use a pre-trained network as a feature ...
