Scientists believe they have found a new use for facial recognition technology: saving large sea animals called seals.
Researchers from Colgate University in the US state of New York developed SealNet. The system is a database of seal faces created by taking pictures of numerous harbor seals in Casco Bay, Maine.
The research team found that the tool precision in the identification of mammals was close to 100%.
The researchers are working to increase the size of their database to make it available to other scientists, Krista Ingram said. She is a professor of biology at Colgate and a member of the team.
Increased database to include rares species such as the Mediterranean monk seal and the Hawaiian monk seal could contribute to efforts to save these species, she said.
Creating a list of seal faces and using machine learning to identify them can also help scientists learn where seals are in the ocean, Ingram said.
She said: “For marine mammals that move around a lot and are difficult to photograph in water, we need to be able to identify individuals.”
SealNet is designed to identify the face in a photo. It recognizes the seal’s face based on information about the shape of the eyes and nose, just as it would for a human. A similar tool called PrimNet, intended for use on primateshad been used on seals before, but SealNet worked better, the Colgate researchers said.
The Colgate team published their findings last spring in Ecology and Evolution. They processed more than 1,700 images of more than 400 individual seals, according to the newspaper.
The paper said SealNet software could be a valuable tool in the developing field of “conservation technology” – technology aimed at saving and protecting wild animals.
Harbor seals are a conservation success story in the United States More than 100 years ago, the animals were once widely killed. But the Marine Mammal Protection Act, which turned 50 in October, gave them new protections – and populations have started to return.
Seals and other marine mammals have long been studied using satellite technology. Using artificial intelligence to study them is one way to bring conservation into the 21st century, said Jason Holmberg of Wild Me. The Oregon-based company is working to bring machine learning to biologists . Wild Me is developing a possible partnership with SealNet.
Harbor seals are now common in the waters off the coast of the northeastern United States. However, other seal species remain at risk. The Mediterranean monk seal is considered the most endangered seal in the world with only a few hundred animals left.
Facial recognition technology could provide valuable data, said Michelle Berger, associate scientist at the Shaw Institute in Maine. Berger was not involved in the SealNet research.
“Once the system is perfected, I can imagine many interesting environmental uses,” Berger said. “If they could recognize seals and recognize them from year to year, that would give us a lot of information about movements, how much they move from site to site.”
Colgate researchers are also working with FruitPunch, a Dutch company artificial intelligence company, to improve parts of SealNet to help more scientists use it, said Tjomme Dooper, FruitPunch’s head of partnerships and growth.
This would open up new opportunities to study animals and help protect them, he said.
“What this does is help biologists study the behavior of seals, as well as the population dynamic“, said Dooper. He added that harbor seals give important information about the environment around them.
I am John Russell.
Patrick Whittle reported this story for The Associated Press. John Russell adapted it for VOA Learning English.
words in this story
species – nm biology: a group of animals or plants that are similar and can produce young animals or plants
precision -not. absence of error or errors
primate – nm any member of the animal group that includes humans, great apes, and apes
conservation – nm the protection of animals, plants and natural resources
artificial intelligence -not. a field of computer science that involves giving machines the ability to appear to have human intelligence
dynamic – nm the way two or more people or things behave with each other due to a particular situation
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