Artificial intelligence is one of the newest and most exciting fields of technology and is quickly being adopted worldwide. It has potentially limitless uses and can be applied to virtually every industry and business worldwide, besides being helpful in most people’s day-to-day lives. Software developers and engineers have been able to combine complex algorithms and theories to create artificial intelligence bots that have the capacity to think similarly to humans and can learn from their mistakes. However, the cornerstone of this technology has been researched and developed most extensively: computer vision.
What is computer vision?
Computer vision is one of the most complicated yet important features that modern AI is equipped with, and perhaps it helps them function in the real world above all others. Simply put, it gives AI the ability to see and interpret things it sees in the real world, just like humans. Using computer vision, these bots can connect what they see through cameras and hear through microphones to existing databases, interpreting, filing, and categorizing all the images they see until those images make “sense.” This way, based on their body language, an AI can tell when a traffic light is red or green and when a user is upset or happy.
Computer vision is an incredibly delicate and complex technology that has a lot of core components, all of which are needed to make it work effectively. This includes image preprocessing, in which the bot will file an image into a broad category in a fraction of a second so that it can be interpreted faster later. Feature extraction is the next step, and AIs use this technology to enhance and focus on the main points of interest in an image. A combination of deep machine learning algorithms learns from this task each time it’s performed to make things faster the next time. Another core component is convolutional neural networks.
Applications of computer vision in robotics
Computer vision has a lot of potential applications in robotics, but it is already being used to overhaul countless systems, including security and policing. Streaming and social media websites can classify new videos and images posted into categories to recommend them to users and remove potentially harmful or criminal content. Government agencies use images from traffic cameras or security footage to recognize criminals or persons of interest.
Deep learning algorithms have been able to improve machines that are used in medical contexts, such as those used in conjunction with X-rays and MRIs. These machines can efficiently detect points of interest in medical images, including potential tumors, hemorrhages, and congenital defects. This technology has allowed medical professionals to speed up the patient care process, freeing up the doctor’s time to deal with patients individually and provide them with more focused care. They’re also able to detect potentially rare diseases thanks to a database that is connected with medical centers all over the world.
Some of the most exciting possibilities of machine learning are coming shortly, as more adoption and use have helped accelerate AI development. These applications include self-driving vehicles, using computer vision and neural networks to safely detect obstacles, road signs, and pedestrians. Their use in aircraft could further reduce the risk of plane accidents, and their integration into applications may allow better user experiences as companies can develop software faster. Small businesses may be able to use this technology to develop products with higher scalability.
Artificial intelligence is a technology that people wouldn’t have dreamt possible even a few decades ago. It’s an invention straight out of science fiction, and its existence at the scale it’s currently on in society is even more surprising. Such technology requires hundreds of millions of dollars and the top minds in software design and engineering to create and improve upon. One of the main tools developed for AIs, similar to the most popular chatbots on the internet, is computer vision. It’s important to understand how this tool is utilized so you can take advantage of it, too. Using the information in this article, you can understand AI better and implement your findings in your own work.