Capsule networks
Capsule Networks (CapsNets) are a very recent and innovative type of deep learning network. This technique was introduced at the end of October 2017 in a seminal paper titled Dynamic Routing Between Capsules by Sara Sabour, Nicholas Frost, and Geoffrey Hinton (https://arxiv.org/abs/1710.09829) [14]. Hinton is the father of Deep Learning and, therefore, the whole Deep Learning community is excited to see the progress made with Capsules. Indeed, CapsNets are already beating the best CNN on MNIST classification, which is ... well, impressive!!
So what is the problem with CNNs?
In CNNs each layer "understands" an image at a progressive level of granularity. As we discussed in multiple examples, the first layer will most likely recognize straight lines or simple curves and edges, while subsequent layers will start to understand more complex shapes such as rectangles up to complex forms such as human faces.
Now, one critical operation used for CNNs is...
