I am reading the paper with the title Classification of indoor actions through deep neural networks. And I came across this statement:With this mechanism very complex functions can be learned combining  these modules: the resulting networks are often very sensitive to  minute details and insensitive to large irrelevant variations.I have read a lot about deep neural network. However, I might have missed the logic behind why deep neural networks are insensitive to large irrelevant features.
How neural networks handle large variations in the input?
neural network;deep learning