The computer vision state

In this section, we will look at how computer vision has grown over the past couple of years into the current field of computer vision we have today. As mentioned before, the progress in the field of deep learning is what propelled computer vision to advance.

Deep learning has enabled a lot of applications that seemed impossible before. These include the following:

• Autonomous driving: An algorithm is able to detect the location of pedestrians and other cars, helping to make decisions about the direction of the vehicle and avoid accidents.
• Face recognition and smarter mobile applications: You may already have seen phones that can be unlocked using facial recognition. In the near future, we could have security systems based on this; for example, the door of your house may be unlocked by your face or your car may start after recognizing your face. Smart mobile applications with fancy features such as applying filters and grouping faces together have also improved drastically.
• Art generation: Even generating art will be possible, as we will see during this book, using computer vision techniques.

What is really exciting is that we can use some of these ideas and architectures to build applications.