by Angela Guess
Hannah Augur recently wrote in Dataconomy, “Deep Learning is one of the key parts of data science. As data becomes increasingly important and accessible, today’s biggest companies are rapidly investing in deep learning. In fact, it is considered to be so vital to future technologies that many are sharing their own results and discoveries with the public. Researchers have been playing with the idea of deep learning for decades, but it has only blossomed in recent years. With companies like Facebook and Google pouring funds and resources into research, consumers are finally seeing the results of deep learning for themselves. Rather than staying behind closed doors, ordinary folks are already face-to-face with deep learning and don’t even know it.”
Augur goes on, “DeepFace. The appropriately named project from Facebook is ‘closing the gap to human-level performance in face verification.’ If you’ve ever gone to tag a picture, only to have completely random name pop up, you’ve experienced poor facial recognition. The inabilities of current recognition software has created a population that simply distrusts it entirely, and has spawned plenty of failure compilations and web articles. Many facial recognition programs use thousands of engineered features to fuel the recognition process. DeepFace, on the other hand, is based in the development of an effective deep neural net that leverages a huge dataset of faces, allowing them to have a real understanding of general traits and features.”
photo credit: Flickr/ bixentro