In this article we will share with you an in-depth and extensive overview of Computer vision, one of the key fields of artificial intelligence (AI).
Artificial intelligence has enabled computer systems to analyze digital images, videos and other visual inputs with computational methods. This is used to derive information that can be used to make decisions based on that information.
So, having said that, what is computer vision?
As the viso.ai article explains, it is a field of Artificial Intelligence (AI), which deals with computational methods to help computers understand and interpret the content of digital images.
Thus, Computer vision aims to make computers see and understand visual data input from cameras or video sensors. This is to help computers automatically understand the visual world by simulating human vision using computational methods.
The value of computer vision
Computer vision systems are able to inspect products, monitor infrastructure or a production asset to analyze thousands of processes in real time, noting defects or problems. Due to its speed, continuity, accuracy and scalability, it can quickly surpass human capabilities.
The latest deep learning models achieve above human-level accuracy and performance in image recognition tasks such as: Face recognition, object detection and image classification.
Computer vision applications are used in a wide range of industries, ranging from security and medical imaging to manufacturing, automotive, agriculture, construction, transportation, smart city and many more. As the technology advances and becomes more flexible and scalable, more use cases become possible.
Did you know that according to a report (2021) by Verified Market Research , the computer vision AI market size was valued at USD 7 billion in 2020 and is forecast to reach USD 144 billion by 2028, growing at a compound annual rate of 45% from 2021 to 2028?
How does computer vision work?
Generally, computer vision works in three basic steps:
- Acquire the image/video from a camera.
- Process the image
- Understand the image.
And now a practical example of computer vision
Computer vision requires a large amount of data to train a deep learning algorithm that can accurately recognize images.
For example, to train a computer to recognize a hat, it needs to be fed large amounts of images of hats, with people wearing hats in different scenes to learn the characteristics of a hat.
Then, the trained algorithm can be applied to newly generated images, e.g., videos from surveillance cameras, to recognize a hat.
By understanding the visual world, it is possible to recognize fraud attempts in the insurance industry, as well as speed up the claims settlement process.
All of this is a reality at LISA Insurtech, as we have taken the most cutting-edge technology to offer documentary and photographic analysis in all claims settlement processes, thanks to the help of our artificial intelligence, Burns.