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Not even scientists can tell these birds apart. But now, computers can

Science – “It’s a fact of life for birders that some species are fiendishly difficult to tell apart—in particular, the sparrows and drab songbirds dubbed “little brown jobs.” Distinguishing individuals is nearly impossible. Now, a computer program analyzing photos and videos has accomplished that feat. The advance promises to reveal new information on bird behaviors…So team member André Ferreira, a Ph.D. student at the University of Montpellier, decided to try a kind of artificial intelligence. The tool, called a convolutional neural network, sifts through thousands of pictures to figure out which visual features can be used to classify a given image; it then uses that information to classify new images. Convolutional neural networks have already been used to identify various plant and animal species in the wild, including 48 kinds of African animals. They have even achieved a more complicated task for elephants and some primates: distinguishing between individuals of the same species. Ferreira fed the neural network several thousand photos of 30 sociable weavers that had already been tagged. “No one had come up with an efficient method to collect these training data sets,” he says. To take the photos, he set up cameras near bird feeders equipped with radio-frequency antennas. As soon as the birds landed, a small computer recorded their identity using their PIT tag, and a camera snapped pictures of their backs every 2 seconds. (The rear view is the part of the bird seen most often while they are nesting or foraging.) After just 2 weeks, Ferreira had enough photos to train the neural network. “We were not sure if it would work,” Doutrelant recalls. “We have observed these birds a lot, and we’ve never managed to recognize them without the color rings.” But when given photos it hadn’t seen before, the neural network correctly identified individual birds 90% of the time, they report this week in Methods in Ecology and Evolution. Doutrelant says that’s about the same accuracy as humans trying to spot color rings with binoculars…”

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