How does computer vision work?

Question

Explain the working of this field.

Answer 1

WORKING: 

(1) (a) Computer vision needs lots of data. 
(b) It runs an analysis of data over and over until it discerns distinctions and ultimately recognizes images. 

• For example, to train a computer to recognize automobile tires, it needs to be fed vast quantities of tire images and tire-related items to learn the differences and recognize a tire, especially one with no defects.

(c) Two essential technologies are used to accomplish this:

• a type of machine learning called deep learning and
• a convolutional neural network (CNN).

(2) (a) Machine learning uses algorithmic models that enable a computer to teach itself about the context of visual data. 
(b) If enough data is fed through the model, the computer will “look” at the data and teach itself to tell one image from another. 
(c) Algorithms enable the machine to learn by itself, rather than someone programming it to recognize an image.

(4) (a) A CNN helps a machine learning or deep learning model “look” by breaking images down into pixels that are given tags or labels. 
(b) It uses the labels to perform convolutions (a mathematical operation on two functions to produce a third function) and makes predictions about what it is “seeing.”
(c) The neural network runs convolutions and checks the accuracy of its predictions in a series of iterations until the predictions start to come true.
(d) It is then recognizing or seeing images in a way similar to humans.

• _{Study More about Computer Vision at - Computer Vision Class 10}