
The solution to complexity is abstraction, also known as information hiding. Abstraction is simply the removal of unnecessary detail. The idea is that to design a part of a complex system, you must identify what about that part others must know in order to design their parts, and what details you can hide. The part others must know is the abstraction.
This type of classifier takes a tiny portion of labeled data and a much larger amount of unlabeled data (from the same domain). The goal is to combine these sources of data to train a Deep Convolution Neural Networks (DCNN) to learn an inferred function capable of mapping a new datapoint to its desirable outcome.