Scientists at Duke University and the Wildlife Conservation Society (WCS) used a deep-learning algorithm, a form of artificial intelligence, to analyze more than 10,000 drone images of mixed colonies of seabirds in the Falkland Islands off Argentina's coast.
The Falklands, also known as the Malvinas, are home to the world's largest colonies of black-browed albatrosses, and second-largest colonies of southern rockhopper penguins. Hundreds of thousands of birds breed on the islands in densely interspersed groups.
The deep-learning algorithm correctly identified and counted the albatrosses with 97% accuracy and the penguins with 87%. All told, the automated counts were within 5% of human counts about 90% of the time.
The Science Daily website quoted Madeline C. Hayes, marine biology professor at the Duke University, as saying: "Using drone surveys and deep learning gives us an alternative that is remarkably accurate, less disruptive and significantly easier. One person, or a small team, can do it, and the equipment you need to do it isn't all that costly or complicated."
To conduct the new surveys, WCS scientists used an off-the-shelf consumer drone to collect more than 10,000 individual photos, which Hayes' team converted into large-scale composite visual using image-processing software.
They then used a type of AI that employs a deep-learning algorithm to analyze an image and differentiate and count the objects it "sees" in it -- in this case, two different species of sea birds.
These counts were added together to create comprehensive estimates of the total number of birds found in the studied colonies.
