In data science, a convolutional neural network (CNN) is specific kind of deep learning architecture that uses the convolution operation to extract relevant explanatory features for the input image. CNN layers are connected as a feed-forward neural network while using this convolution operation to mimic how the human brain functions while trying to recognize objects. Individual cortical neurons respond to stimuli in a restricted region of space known as the receptive field. In particular, biomedical imaging problems could be challenging sometimes, but in this chapter, we'll see how to use CNN in order to discover patterns in this image.
The following topics will be covered in this chapter:
- The convolution operation
- Motivation
- Different layers of CNNs
- CNN basic example: MNIST digit classification
