Powering Human Analytics Through Deep Learning.

What is Artificial Intelligence?

A.I.(Artificial Intelligence) is all around us. In fact, it seems like every week there is a new breakthrough in the field and a new record set in some task previously done by humans. Advancements in computing are pushing progress quicker than ever.


Not too long ago A.I. may have seemed a distant dream to researchers. Today it is a part of our daily life. Just take a look at some of the apps you use every day:

  • A.I. powered predictions make navigation apps possible.
  • Features we have come to rely on in mobile banking are based on A.I. systems.
  • Social media's use of neural networks to power facial recognition and contextual learning to understand the content of posts.

Deep learning is quickly becoming a part of our everyday life.

What makes A.I. possible?


Gives "Computers the ability to learn without being explicitly programmed"

Arthur Samuel, American pioneer in the field of computer gaming & artificial intelligence, he coined the term "machine learning" in 1959

Machine learning is an application of artificial intelligence that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves. The process of learning begins with observations or data, Such as examples, direct experience or instruction, in order to look for patterns in data and make better decisions in the future based on the examples that we provide.

The primary aim is to allow computer programs to learn automatically without human intervention or assistance and adjust actions accordingly.


Machine vision is the technology and methods used to provide imaging-based automatic recognition and analysis for such applications as automated inspection.

Definitions of the term "machine vision" vary, but all include the technology and methods used to extract information from an image, as opposed to image processing, where the output is another image.

For example, the information extracted and quantified in a 2D image can be a wrinkle, pore, acne, pigmentation etc.

In the 3-dimensional space additional structures can be measured, such as sagging of the jowl, perioral wrinkles, nasolabial folds etc.

The primary aim is to allow the computer program's algorithms to detect; extract and quantify automatically without human intervention or assistance.


Combining machine learning and machine vision techniques, DeepView is able to tap into BTBP's DeepTag platform to decode and provide detailed analysis of photos. DeepView Offers insights and analytics to address common challenges for clinical research and claims substantiation.

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