Ed Miller and Mary Nguyen are Silicon Valley software developers by day, but moonlight at solving an unusually fuzzy problem. A few years ago the pair became mesmerized, like many of us, by an Alaskan webcam broadcasting brown bears from Katmai National Park. They also happened to be seeking a project to hone their machine learning expertise. "We thought, machine learning is really great at identifying people, what could it do for bears?" Could artificial intelligence used for face recognition be harnessed to discern one bear face from another?

From 4,675 fully labeled bear faces on DSLR photographs, taken from research and bear-viewing sites at Brooks River, Ala., and Knight Inlet, they randomly split images into training and testing data sets. Once trained from 3,740 bear faces, deep learning went to work "unsupervised," Dr. Clapham said, to see how well it could spot differences between known bears from 935 photographs. First, the deep learning algorithm finds the bear face using distinctive landmarks like eyes, nose tip, ears and forehead top. Then the app rotates the face to extract, encode and classify facial features. The system identified bears at an accuracy rate of 84 percent, correctly distinguishing between known bears such as Lucky, Toffee, Flora and Steve.