Each day billions of photographs are uploaded to photo-sharing services and social media platforms, and Cornell computer science researchers are figuring out ways to analyze this visual treasure trove through deep-learning methods. Kavita Bala, professor of computer science; Noah Snavely, associate professor computer science at Cornell Tech; and Kevin Matzen, M.S. '15, Ph.D. '16, have released their results in a new paper, "StreetStyle: Exploring world-wide clothing styles from millions of photos." "We present a framework for visual discovery at scale, analyzing clothing and fashion across millions of images of people around the world and spanning several years," Snavely said. Bala said the group used deep learning to detect various attributes – the color or sleeve length of shirts, whether a person is wearing glasses or a hat, and so on – in millions of images. "Using these detected attributes, we can then derive visual insight," Bala said.