Improving performance for classifying images

After introducing transfer learning and fine-tuning in the previous recipe, in this one, we will apply it to image classification, a CV task.

In the second recipe, Classifying images with MXNet – GluonCV Model Zoo, AlexNet, and ResNet, in Chapter 5, Analyzing Images with Computer Vision, we saw how we could use GluonCV to retrieve pre-trained models and use them directly for an image classification task. In the first instance, we looked at training them from scratch, effectively only leveraging past knowledge by using the architecture of the pre-trained model, without leveraging any past knowledge contained in the pre-trained weights, which were re-initialized, deleting any past information. Afterward, the pre-trained models were used directly for the task, effectively also leveraging the weights/parameters of the model.

In this recipe, we will combine the weights/parameters of the model with the target dataset, applying the...