April 2018
Beginner to intermediate
282 pages
6h 52m
English
We discussed feed-forward neural networks in an earlier section. Though they are powerful, one of their main disadvantages is that an FNN ignores the structure of the input data. All data feed to the network has to be first converted into a 1D numerical array. However, for higher-dimensional arrays such as in an image, it gets difficult to deal with such conversion. It is essential to preserve the structure of images, as there is a lot of hidden information stored inside the, this is where a CNN comes into the picture. A CNN considers the structure of the images while processing them.
The next question that we have is the difficult term-convolution. What is it?