Convolutional Neural Networks
When we talk about computer vision, we talk about CNNs in the same breath. CNN is a class of deep neural network that is mostly used in the field of computer vision and imaging. CNNs are used to identify images, cluster them by their similarity, and implement object recognition within scenes. CNN has different layers— namely, the input layer, the output layer, and multiple hidden layers. These hidden layers of a CNN consist of fully connected layers, convolutional layers, a ReLU layer as an activation function, normalization layers, and pooling layers. On a very simple level, CNNs help us identify images and label them appropriately; for example, a tiger image will be identified as a tiger:
Figure 7.1: A generalized CNN
The following is an example of a CNN classifying a tiger:
Figure 7.2: A CNN classifying an image of a tiger into the class "Tiger"
