Can AI Models Stan BTS? Yes, they can Even Go Crazy for the Stars!

Training an AI model stan BTS members! Yes, now even the k-pop buzz is impacting technology

Well, who cannot stan BTS? But extending it to an AI model has caused quite a stir on the internet as BTS fans or 'Armys' are showering their enthusiasm and love towards this initiative. As we know, artificial intelligence is one of the most widely used technologies that is adopted by large tech companies and common individuals to make their professional and personal lives easier. Its adjoining technologies like machine learning, edge, and face detection have not only won over global industries but have also impressed tech critics. After years of evolution and development, it is safe to say that AI has turned out to be the future of humankind itself! Now, tech experts are specifically training an AI model stan BTS, the South-Korean boyband that is breaking global records currently, and more major celebrities. 

The rising adoption of facial recognition technology based on AI platforms uses machine learning algorithms to identify or verify a person from a digital image or video source. But there have been several controversies revolving around deploying facial recognition technology since there is very little information on how it actually works. Several companies have stopped using face detection systems, even for security purposes, since there have been questions about the technology's legitimacy in securely storing information. But nevertheless, experts are using face detection software to realize how it actually works and training it to specifically recognize one person.

So, who made this miracle possible of training a face recognition software to stan BTS?

Well, Sabrina Cruz, a YouTuber, best known for posting videos on her channel named 'Answer in Progress' posted a video where she trains face detection software to recognize and detect BTS members from digital videos and images. She focused on training the model to identify the numerical representation of their faces and detect the unique features that make their faces distinct using the histogram of oriented gradients. She also thoroughly decoded how facial recognition software works and explained it to her audience. This is just the beginning of such an advancement. Kudos to Sabrina!