Facial recognition may help conserve seals, scientists say

Facial recognition may help conserve seals, scientists say

FREEPORT, Maine (AP) — Facial recognition technology is primarily associated with uses like monitoring and authenticating human faces, but scientists believe they’ve found a new use for it — saving seals.

A research team from Colgate University has developed SealNet, a database of seal faces created by taking pictures of dozens of harbor seals in Casco Bay, Maine. The team found that the tool’s accuracy in identifying marine mammals is close to 100%, which is no small feat in an ecosystem home to thousands of seals.

The researchers are working to expand their database to make it available to other scientists, said Krista Ingram, Colgate biology professor and team member. Expanding the database to include rare species such as the Mediterranean monk seal and the Hawaiian monk seal could help inform conservation efforts to save these species, she said.

Cataloging seal faces and using machine learning to identify them can also help scientists get a better idea of ​​where seals are in the ocean, Ingram said.

“Understanding their dispersal, understanding their patterns really helps to inform all coastal conservation efforts,” she said. “For mobile 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 automatically detect the face in an image, crop it, and recognize it based on facial patterns such as the shape of the eyes and nose, as if it were a human. A similar tool called PrimNet, intended for use on primates, had previously been used on seals, but SealNet surpassed it, the Colgate researchers said.

The Colgate team published their findings in April in the scientific journal Ecology and Evolution. They processed more than 1,700 images of more than 400 individual seals, according to the newspaper.

The paper stated that “the ease and richness of image data that can be processed using SealNet software provides a vital tool for ecological and behavioral studies of marine mammals in the developing field of conservation technology. “.

Harbor seals are a conservation success story in the United States. The animals were once subject to bounty in New England, where they were widely considered pests by fishermen in the 19th and early 20th centuries. But the Marine Mammal Protection Act, which turned 50 in October, extended new protections to them – and populations began to rebound.

Seals and other marine mammals have long been studied using satellite trackers. Using artificial intelligence to study them is one way to bring conservation into the 21st century, said Jason Holmberg, executive director of Wild Me, an Oregon-based company that strives to bring machine learning to biologists. Wild Me is developing a potential partnership with SealNet.

“It’s a shift and a step up from ‘big brother’ style technology to a very benevolent conservation style goal,” Holmberg said.

Harbor seals are now quite abundant in New England waters, where they haul out the rocks and delight seal-watching cruises and beachgoers. However, other seal species remain threatened. The Mediterranean monk seal is considered the most endangered seal in the world with only a few hundred animals left.

Using facial recognition could provide more valuable data, said Michelle Berger, an associate scientist at the Shaw Institute in Maine, who was not involved in the SealNet research.

“Once the system is perfected, I can imagine many interesting ecological applications,” 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 artificial intelligence company, to improve certain aspects of SealNet to encourage wider use. FruitPunch is asking a few dozen scientists around the world to take on the challenge of streamlining SealNet’s workflow, said Tjomme Dooper, FruitPunch’s head of partnerships and growth.

Improved automation of facial recognition technology could make SealNet more useful to more scientists, Dooper said. This would open up new opportunities to study animals and help protect them, he said.

“It helps biologists study seal behavior, as well as population dynamics,” Dooper said. “Harbour seals are an important indicator species for the ecosystem around them.”

Follow Patrick Whittle on Twitter: @pxwhittle

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