Computer vision is a field of artificial intelligence that is concerned with the automatic extraction and analysis of useful information from images. This technology being impressive in its own right, there is fundamental disruption here in terms of what it means in understanding risk and labeling operation.

So we are living in a world where cars are beginning to drive themselves and the most profound liabilities and confirmation of recovery are being done by sensors that were never applied before. With computer vision, imaging can be tied to fundamental risk.

How Does Computer Vision Work?

In terms of how all this work, it is the underlying technology that is enabling these fascinating applications is that of neural networks.

Neural networks are a set of algorithms in machine learning that enable computer vision. An insight into how this work is having an image that is projected onto simulated neurons taking inputs of light and the first level of processing is projected back and it is in that area you see the first level of pattern detection and that is what these technologies are fundamentally about. What that means is the network is learning what an eye looks like; going up a level you have prototypical faces and this is all encoded in this network.

Now eventually it gets propagated up to an actual entity or a decision to be made. What has been done in the laboratory is now brought into the industry because we have advanced in computational power.

Challenges of Implementing These Advanced Technologies

The first one is regarding data silos; in terms of access to data something as seemingly innocent as social media data cannot be brought into the existing operation.

Another major challenge is the talent gap; you need the domain, the engineering and that process excellence geared with the data science, getting all the skills together is an absolutely major challenge. The third challenge is simply courage; these applications will become in some variant the dominant way to do a business operation. The question is who has the courage to attempt them, to operationalize them. and lead the industry. You need some way to put on modern algorithms bound with affordable compute power to actually extract core aspects of that data specific to the new space. So it’s highly collaborative and it is a binding of the use case of a domain, data, and discovery; and the winners are going to be those that figure out these use cases first.

Application of Computer Vision

Computer vision is an emergent technology that is embedded in different devices we use in our daily life. For example, we can find it in any of the multiple cameras we have in our mobile phones, tablets, or photo cameras. It is also in the games we play, in identity-based access control systems, a supporting medical diagnosis, surgery assistance, and for smart interfaces among other industrial sectors. Computer vision deals with the problem of understanding automatically generated images or video content, this is an ability that we humans perform in almost unconscious manner but it is a big deal for computers. A lot of new software and hardware engines will come out to be integrated with new smart devices such as smart glasses or in smart cars that will run on our roads in the near future.