“Albert Einstein said once: “The significant problems we have, cannot be solved at the same level of thinking with which we created them”, but in today’s changing technology-driven realm, the answer to such problems is achievable with Artificial intelligence. “
Automated
or Automatic Image recognition is looked upon as the branch of
Artificial Intelligence heading the foremost digital trends nowadays.
Bearing
in mind today’s scenario, wherein Artificial Intelligence can currently
identify faces with 97.5% accuracy, it is actually faster than any
another conventional technology. Thus, humans facial recognition has
evolved widely over time. Considering an example of learning visual
identification and using it, chess players who learn playing chess from a
young age learn configuration patterns and choices available on the
board. With the powers of pattern detection and recognition, they can
defeat less worthy opponents.
Now,
let’s consider an example of similar learning computers, which divide
the facial image data among visual nodal points, depth of body cavities,
distance between eyes, nose breadth, and actually draw distinctive
features of a person’s face quite effortlessly for matching faces with
similar depth and data flux.
AI recognition: We are at the beginning of a digitalized world!!!
• Automated Image recognition
by computers actually clicks a person’s picture and creates a 3D-model
with the features noticeable in a more prominent manner. With this
technology, pictures taken from different angles and poses are recorded
for future use in facial recognition.
•
With the prominence of deep learning in Artificial intelligence, all
aspects of AI recognition align well with the requirements of the
industry, all thanks to “Neural networks”- a framework for handling different machine learning algorithms and figuring out information inputs together.
• Facebook’s neural network has 20 million connections, with a stored library of 4.4 million visible faces, and increasing every moment.
•
Image recognition can be used for security tracking from the
traditional image recognition systems, which are based on 2-D systems.
With the preference among technology companies like Google and Apple to
facilitate “smart business” & “smart living”, Automated Image
recognition is a boom for them!
• Smart search:
Machine-controlled “scan-to-buy” programs have been introduced across
physical stores as well as other shops wherein the shoppers can utilize
the options of scanning products and transferring cash without waiting
in long queues.
With
the payment system backed by automatic face recognition features, it
conjointly adapts the shoppers into paying and existing rapidly.
• Smart hotels:
Some of the leading hotels manage advanced cloud and Artificial
intelligence technologies, social networks and payment tools. What makes
these hotels “smart” is that guests can book rooms, sign on remotely
and use their phones as key cards – all on the image recognition enabled
app.
• Medical robots for surgeries:
Specialized pharmacies and hospitals across countries are now using
robots which have pre-defined computer codes for granting initial
analysis of customers’ symptoms and recommended prescriptions. Once you
seek the recommendation from the doctor the patient’s bill gets passed
over to the counter for dispensing medications also now surgeries are
dependent half of time on the robotics hands that follow the command
and rarely make any mistake.
• Genre and age detection: AI
can not only name the person but can also perceive their information.
Thus, AI detects the information in person such as age and genre from a
given static files.
• Visual Search: Another
very important part of AI is Visual observation and analysis in this
AI itself understands to find visually exact and similar matches to an
image from a database of images. Automated Image is perfect in
replicating the most natural way of providing perfect visual search
results.
Artificial Intelligence: The latest technology
Stephen Hawking said to the BBC during an interview that “The development of full artificial intelligence could spell the end of the human race!” That day is still far off, we think. AI image recognition is being used in helpful ways, like Microsoft’s Earth Lens which uses Artificial intelligence to find objects in satellite pictures.
Among
the most recent inventions of Microsoft, it leverages Artificial
intelligence to pinpoint features in satellite imaging. Earth Lens
launched in open source identifies, tracks, and analyzes objects in
photos taken from miles high off the planet’s surface.
Conclusion:
AI computer vision and image recognition
is meant to achieve a specific goal thus by communicating with humans
and by recognizing their surroundings. Where computer vision gives it
the sense of prospects of the thing, image recognition helps in
understanding the physical universe and universal things around us.
That’s
another reason why tech companies are investing in facial recognition
and are publicly supporting R&D in this domain. Also, see IBM
recently released a huge image-based dataset that can be used for
training machine learning algorithm’s and neural networks to better
tackle facial recognition problems.
