The power of artificial intelligence is becoming stronger each year. Here’s what the future of AI powered image recognition may actually look like.
Teaching technology to be able to see has been an enormous challenge. This major technological breakthrough promises to be a revolution.
It has already found its way onto Facebook, where an evolved image recognition algorithm can identify the faces of existing members with a 98% accuracy.
AI-powered image recognition is the game-changing technology that lies behind many significant advancements from the cataloging of image databases through to driverless-cars.
We are only just seeing the start of artificial intelligence using image identification. The technology promises so much more.
But what does the future hold for AI image recognition?
Teaching Machines to See
Attaching a camera to a device does not automatically mean that it can see. Developing a machine’s ability to see the world and identify things as a human does has taken considerable effort.
The human eye reads an image as a set of signals. These are processed in the brain’s visual cortex. The images are linked in the mind with memories of objects and visual concepts. From this, we understand what we are looking at.
Image recognition seeks to mimic this brain activity. However, a computer will either see images as Raster images made up of pixels with numerical values for colors or as vector images, which are polygons.
Using this data, it is possible for computers to classify the image by comparing the data to previously categorized examples.
There are countless advantages to having technology that can see and make an assessment of everything in their view. There will be uses in fault detection in places where human eyes can’t see.
But, in addition to an AIs ability to learn, it will be possible for machines to learn to fix previously unknown defects.
Applications for Image Recognition in Education
Image recognition has uses in the classroom. It can be used to enhance the understanding of images for visually impaired students, or those with learning disabilities who may struggle to read or comprehend images.
Schools can use facial recognition technology to take automated attendance.
Some schools in the US have begun using image recognition in the fight against school shootings. Using AI software, it is possible to identify students brandishing weapons or to warn of unusual behavior.
Powering Driverless Cars
Autonomous vehicles promise to reduce the number of automobile deaths by 300,000 over ten years. There are currently over forty different companies developing their own self-driving cars.
At the heart of this technology lies the vehicle’s ability to perceive the road and any changes in the vicinity, which pose a risk.
The AI will be trained to use computer vision to spot hazards such as objects in the road, other vehicles, and pedestrians. The technology can even work in the dark and work out the speed of other moving vehicles.
Once a hazard has been perceived, the computer will be able to react quicker than a human would and make the exact changes to the way that the vehicle is driving to avoid a collision.
Cataloging and Filtering Images
In an internet full of images, many of which have been uploaded by users, filtering and sorting theses images into categories is a challenge for any business.
However, it is essential that images are checked for relevance and appropriateness. With spammers and fraudsters trying to take advantage, AIs can weed out inappropriate images by using an advanced Google image search as a reference point to help identify the content of images.
Improving the Accuracy of Iris Recognition
Iris recognition is a technology that has been in use for a few years now. With application in areas such as passport control for biometric scanning, the technology has found its way into consumer electronic devices such as smartphones.
Biometric facial recognition has been helping secure smartphones for the last couple of years. However, this is still a developing technology, and greater accuracy will come in time.
Iris recognition will find its way into many other areas of our lives, and as it does, it will become more refined and more accurate.
With imaging playing a major part in the healthcare industry, there is great scope to use artificial intelligence and image recognition to improve the accuracy of diagnoses.
Using smart image recognition technology, detecting life-threatening diseases, including cancer, will be made easier.
Improving the Gaming Experience Using Augmented Reality
Augmented reality uses cameras to take images of the world as we see it and bring in on-screen digital imagery to interact with real life.
This technology has been growing in popularity over the last few years, with games such as Pokemon Go being popular and successful uses of this technology.
However, augmented reality, coupled with image recognition, can lead to a more enhanced and realistic world within video games.
AI-Powered E-Commerce Search
If you are out on a train and you see someone wearing a jacket that you like the look of, but you are unsure of where you can buy it. You take out your phone and start to look online for it. You may try your best to try and describe the jacket in your search. Chances are, you won’t find it.
There is an easier way. Rather than basing the search on textual information, you could run a visual search to look for retailers that sell matching items.
With far-reaching implications for online retailers to increase their sales, there will be great incentives to see this technology developed and implemented into apps and e-commerce websites.
It is estimated that by 2021 e-commerce sites that adopt visual search technology early will see a 30% increase in their sales.
The Future Is Visual
Image recognition will play a huge part in informing artificial intelligence. In an increasingly visual world, there will be countless applications for this technology. The only limits are our own imaginations.
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