Can a computer identify bird species in photos? Researchers at Cornell Tech and Caltech have partnered with the Cornell Lab of Ornithology to train Merlin Bird Photo ID to recognize 650 of North America’s most common bird species based on images.
Sometimes Merlin gets it right, just like magic. Other times, Merlin gets it wrong–sometimes way wrong. What’s going on behind the scenes–and how can you help us keep improving Merlin’s accuracy?
The challenge: Asking computers to identify bird species is a challenge not only because some species look so alike, but also because their shape varies from moment to moment. On top of that, photographs of birds often include complex backgrounds, and the birds may be far away or blurry.
The solution: Computer vision researchers create “convolutional network” systems that use patterns in data to train the computer and improve its performance. These systems require massive numbers of images as well as accurate image labels such the type of object, and where the object is in the image. Fortunately, bird watchers are renowned for taking lots of photos and for contributing millions of observations in citizen-science projects. Thousands of people have contributed photos and tagged them to teach Merlin to recognize birds."
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