Snapshot Serengeti gets a boost from AI
“Deep learning,” already poised to transform fields from earthquake prediction to cancer detection to self-driving cars, is about to be unleashed on a new discipline — ecology. A team of researchers from Harvard, Auburn University, the University of Wyoming, the University of Oxford, and the University of Minnesota has demonstrated that the artificial-intelligence technique can be used to identify animal images captured by motion-sensing cameras. Researchers applied deep learning to more than 3 million photographs from the citizen-science project Snapshot Serengeti to identify, count, and describe animals in their natural habitats. The system was able to automate the process for up to 99.3 percent of images as accurately as human volunteers. The study was described in a paper published last month in the Proceedings of the National Academy of Sciences. Motion-sensitive cameras deployed in Tanzania by Snapshot Serengeti collect images of lions, leopards, cheetahs, elephants, and other animals. While the images can offer...