Artificial intelligence (AI) continues to shape everything from healthcare to manufacturing. While AI has been around for many decades, recent implementations are game-changers for industries far and wide. It continues to improve, and new fields of AI are unlocking new possibilities.

Take, for example, computer vision. Computer vision is a type of AI that allows computers to process and understand relevant information from visual inputs. Think of it this way: AI helps a computer to think, while computer vision enables it to see and understand.

How It Works

This technology is complex and can require substantial time and financial investment. That's why so many companies rely on a computer vision platform to accelerate the process, lower operational costs, and increase the overall agility of their systems.

Computer vision requires a mountain of data before it can run efficiently. It repeatedly analyzes data until it can identify differences and recognize images. The types of data it processes depend on the final application, but that training is crucial.

Successful implementation relies on two core technologies. The first is machine learning. Machine learning is a model that enables a computer to teach itself about the visual data it processes. It eliminates the need for human programming, and it mimics similar learning processes of the brain.

The second technology is a convolutional neural network or CNN. A CNN analyzes images deeper, breaking them apart into pixels. CNN attaches labels to those pixels and uses them to perform complex operations to determine what visual inputs it sees. The neural network then checks its accuracy until those predictions are correct. That's how computer vision begins to recognize inputs and improve performance.

Applications for Computer Vision

There are many reasons to invest in a computer vision platform. Allowing AI to identify objects and visual patterns benefits many industries. In healthcare, technology can revolutionize medical imaging for diagnostics. It can spot anomalies in radiology, annotate ultrasound images, track surgical devices, and more.

It also has a place in government applications, manufacturing, information technology, and the list goes on. The right platform can help you implement computer vision at your company, taking your operations into a new age of efficiency.

Author Resource:-

Emily Clarke writes about tech for automated annotation, AI labeling, data evaluation and more. You can find her thoughts at computer vision platform blog.