How is Machine Learning used in Image Recognition?

Photo by Possessed Photography on Unsplash

In the article on Artificial Intelligence, Wikipedia states that: “Artificial Intelligence (AI) is intelligence demonstrated by machines, unlike the intelligence of humans and animals, which involves consciousness and emotionality.”

Machine Learning (ML), as a subset of Artificial Intelligence (AI) can learn by itself. It reprograms itself, because it digests more data, to perform its specific task with increasingly greater accuracy. Therefore, ML is successfully used for image recognition.

ML software frameworks and libraries are widely available for image recognition, but may need to be adapted and / or enhanced to suit the needs of the application. ML models cannot be built and trained without datasets of images which will be later recognized. Example of using ML for image recognition varies from simple objects to more sophisticated face recognition or “guessing” what objects can be behind some bigger objects which obstruct the full view.

When it comes to images, essentially ML is trained and used is several ways, but the most known are:

  • Image or Object Detection: is a technology that processes the image and detects objects in it. Often Image Detection is confused with Image Classification. Normal usage of Image or Object Detection is for locating or finding the number of objects in a picture
  • Image Classification: is a process of labeling objects in the image, for example for sorting these objects by certain criteria. It is a more advanced version of Image Detection, since ML can be used to process different images with different objects, detect them, and classify by the type of the item on the picture
  • Image Recognition: is the ability of AI/ML to detect the object, classify it, and recognize it. This type of technology is somewhat close to the human level of image processing. An easy to explain example of image recognition solutions is the face recognition which comes with many smartphone devices. For unblocking the smartphone device, the user would let the device scan his/her face. This is a more complex process because the system has first to detect the face, then classify it as a human face, and only then decide if it belongs to the owner of the smartphone.

We need to understand that Image Detection, Classification, and Recognition technologies are in their early stages. Nevertheless, with usage of ML, we can imagine a near future where humans will not spend useless time finding, for example, their keys — a computer-like system will be activated through a voice command and will quickly perform the search on behalf of the humans.

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Vasile Nedelcu

Vasile Nedelcu

Digital Transformation, Agile Coach, Agile Software Devopment, DevOps, IT Management, IT Portfolio Management, Cloud Computing, Network Virtualization