One particular type of neural network that in machine learning and picture classification is a convolutional neural network. Face Recognition is a prime illustration.
Assume you click on 50 images of a person’s face, each for ten different people. You therefore have 500 images overall, each featuring 10 distinct people. CNN will be able to determine the facial features of each of these ten people if you provide it with this data. And subsequently, using the prior knowledge, it will identify the face in a fresh photo of any one of these ten people.
CNN makes an effort to replicate how people view images with their eyes. If you stop to think about it, you will see that even when seeing a whole picture, your attention can only be focused on one point at a time. After that, we move our focus to the other points, which is how we memorize the key features of a picture or a face and remember it.
CNN is a series of operations that first extracts the most significant features from a given image, and then it turns the entire image into a single row of numbers. which the fully connected ANN classifier is capable of learning.