Automated Image recognition - The Eye of AI

“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.

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