It's not just computer vision, it's Superhuman Vision

Today, computer vision is present almost everywhere: from software that analyses photo archives for marketing teams and photo-journalists to self-driving cars on the roads.

Superhuman computer vision can further detect abstract emotions in visual content, all the while being extremely customizable, easily trainable, and optimised for your 'edge devices'.
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computer vision

What is computer vision?

Computer vision is a field of computer science that enables machines to extract information from visual data (images or videos) in an attempt to replicate the speed and accuracy of the human visual cortex.

Today computer vision is no longer limited to static photographs and scenes. It can analyze video with astonishing accuracy, while real-time facial recognition is built into the majority of smartphones and other security systems.
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Why is everyone talking about computer vision?

Computer vision: Latest tech for everyday business challenges

Computer vision enables machines to recognise objects in much the same way as the human brain. Today, even a smartphone or a laptop computer can run AI-powered software that makes millions of calculations every second. This 'democratization' of computer vision means that nearly any business, whatever its size or industry, can benefit commercially from the technology.

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From the cloud to
the 'edge'

The latest computer vision solutions are far more streamlined, squeezing immense processing power into common 'edge' devices including smartphones, laptops and devices connected to the internet of things.

Instead of uploading huge volumes of training data to the cloud, much of the heavy lifting can be undertaken on-premise to adapt the technology to the precise needs of your business.

In addition, much of the configuration can now be achieved by non-technical users and with less data availability.

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Computer vision, a breakthrough in privacy

Since the earliest days of facial recognition, questions have been asked about the impact of computer vision on citizen privacy.

Recent advances in computer vision have helped allay many of these concerns as the processing power of the so-called edge devices (on-premise hardware and devices) advances at rapid speed.

This means that organizations can retain complete control over their visual archives using in-house solutions instead of relying on a third party platform.

Computer vision for business users

Formerly the preserve of data scientists and software engineers, computer vision tools are increasingly available to business users who can customise the software in a way that specifically meets the needs of their team.

Today, computer vision is putting the latest machine learning technology tools at the fingertips of the workforce. The technology automates time-consuming manual processes, using aesthetic filters to pick out high quality content while automatically keywording images and videos.

Professionals from marketeers to medics can thereby refocus their attention on the core skills that add genuine value to the business. This 'democratization' of computer vision means that nearly any business, whatever its size or industry, can benefit commercially from the technology.
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Computer vision and digital marketing

Marketing agencies are under greater pressure than ever to squeeze every drop of value from marketing software subscriptions, third-party agencies and media libraries. Many are turning to computer vision to drive engagement, increase leads, and boost creativity.

Boost digital advertising

Boost quality of visual content and increase engagement. Select imagery that drives higher click rates and leads.

Connect with influencers

Analyze social media profiles and imagery to connect clients with the best influencers for their campaigns.

Increase client brand value

Analyze massive volumes of visual content to serve up brand-friendly imagery while enabling marketing professionals to focus on creative activities.
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An introduction to computer vision

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Computer vision in digital marketing

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Computer vision and journalism

Computer vision is redefining the way in which journalists and broadcasters work with visual media. By taking over the cumbersome processes of sifting through tons of visual data, computer vision helps them focus on the human side of stories and supports the delivery of more relevant journalistic content.

Empower journalists

Reduce time searching for photography, enabling journalists to focus on reporting.

Publish in minutes

Automatically tag and edit photography from the field, bringing current affairs and sports to consumers round the clock.

Filter out fake content

Analyze massive amounts of disinformation to uncover authentic photographs and video while filtering out deep fakes.
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Basics of computer vision

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Computer vision in journalism

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Press agency case study

Computer vision and stock imagery

Gone are the days of thousand-dollar invoices for exclusive rights to a photograph. Agencies are now moving to a high-volume, low-margin, royalty-free model. For this to be viable, many are adopting computer vision technology to maximize the commercial potential of their libraries.

Make it easier to find images

Tag millions of images with their contents, including emotional context. Maximize visibility of library to customers.

Uncover valuable content

Revisit image archives using aesthetic filters to uncover valuable content missed by human curators.

Expand commercial possibilities

Use facial recognition to identify historical figures or celebrities and expand commercial potential of your archives.

Bring AI to your business.
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