Deep Learning for Computer Vision

The VGG-16 model

The VGG model stands for the Visual Geometry Group from Oxford. The model was very simple and had a greater depth than AlexNet. The paper had two models with 16 and 19 layers depth. All the CNN layers were using 3 by 3 filters with stride and a pad of size 1 and a max pooling size of 2 with stride 2.  This resulted in a decrease in the number of parameters. Though the size is decreasing because of max pooling, the number of filters is increasing with layers. The architecture of the 16-layer deep model is as follows:

This model has 138 million parameters and is the largest of all the models described here. But the uniformity ...