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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…
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. Team member André Ferreira, a Ph.D. student at the University of Montpellier, fed the neural network several thousand photos of 30 sociable weavers that had already been tagged… [W]hen 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. Behavioral ecologist Claire Doutrelant of CNRS, the French national research agency, says that’s about the same accuracy as humans trying to spot color rings with binoculars.
Ferreira then tried the approach on two other bird species studied by Damien Farine, a behavioral ecologist at the Max Planck Institute of Animal Behavior. The tool was just as accurate…
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Source:: Slashdot