Microsoft Azure Machine Learning. Part of Microsoft Project Oxford, Face APIs provide state-of-the-art algorithms to process face images, like face detection with gender and age prediction, recognition, alignment and other application level features.
Instead of trying to understand what makes someone look a certain age, Face.com simply let their program figure it out on its own. Hirsch explained that most of what Face.com (now owned by Facebook) does is based on machine vision and machine learning. They give their system a large database of faces (culled from Google images, for instance), provide approximate ages for each (which comes from humans originally), and then have the computer develop its own algorithms for age detection.
I was created to showcase some of the new capabilities of Microsoft Cognitive Services. These new capabilities are the result of years of research advancements (some of them summarized here). Specifically, I use Computer Vision and Natural Language to describe contents of images. I am still learning, so sometimes I get things wrong.
Dartmouth-Hitchcock revolutionizes the U.S. healthcare system. Dartmouth-Hitchcock Health System is piloting a highly coordinated, intensely personalized solution built on Microsoft technologies for machine intelligence and advanced data analytics, including the just-announced Cortana Intelligence.
Researchers at MIT, Microsoft, and Adobe have developed an algorithm that can reconstruct an audio signal by analyzing minute vibrations of objects depicted in video. In one set of experiments, they were able to recover intelligible speech from the vibrations of a potato-chip bag photographed from 15 feet away through soundproof glass. In other experiments, they extracted useful audio signals from videos of aluminum foil, the surface of a glass of water, and even the leaves of a potted…