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Scientists believe they have found a new use for facial recognition technology: saving large ocean animals known as seals.
科学家认为，他们发现了面部识别技术的新用途：拯救大型海洋动物——海豹。
Researchers at Colgate University in the U.S. state of New York have developed SealNet.
美国纽约州科尔盖特大学的研究人员开发了SealNet。
The system is a database of seal faces created by taking pictures of many harbor seals in Maine's Casco Bay.
该系统是一个海豹面部数据库，其通过拍摄缅因州卡斯科湾的许多港海豹的照片创建的。
The research team found the tool's accuracy in identifying the mammals was close to 100 percent.
该研究小组发现，该工具识别该哺乳动物的准确率接近100%。
The researchers are working on increasing the size of their database to make it available to other scientists, said Krista Ingram.
克里斯塔·英格拉姆说，研究人员正在努力扩大数据库的规模，以便其他科学家可以使用它。
She is a biology professor at Colgate and a team member.
她是科尔盖特大学的生物学教授，也是该研究小组的成员。
Increasing the database to include rare species such as the Mediterranean monk seal and Hawaiian monk seal could help efforts to save those species, she said.
她说，将地中海僧海豹和夏威夷僧海豹等稀有物种纳入数据库可能会有助于拯救这些物种。
Creating a list of seal faces and using machine learning to identify them can also help scientists know where in the ocean seals are, Ingram said.
英格拉姆说，创建海豹面部列表并使用机器学习来识别它们也可以帮助科学家了解海豹在海洋中的位置。
She said, "For...marine mammals that move around a lot and are hard to photograph in the water, we need to be able to identify individuals."
她说：“对于频繁活动、很难在水中拍照的海洋哺乳动物，我们需要能够识别个体。”
SealNet is designed to identify the face in a picture.
SealNet的设计目的是识别照片中的面部特征。
It recognizes the seal's face based on information related to the eyes and nose shape, as it would a human.
它根据与眼睛和鼻子形状相关的信息来识别海豹的面部，就像识别人类一样。
A similar tool called PrimNet, that is for use on primates, had been used on seals earlier, but SealNet performed better, the Colgate researchers said.
科尔盖特大学的研究人员表示，一种名为PrimNet的类似工具用于灵长类动物，之前也曾用于海豹，但SealNet的效果更好。
The Colgate team published its findings last spring in Ecology and Evolution.
科尔盖特大学研究小组去年春天在《生态学与进化》杂志上发表了他们的研究结果。
They processed more than 1,700 images of more than 400 individual seals, the paper said.
该论文称，他们处理了400多只海豹的1700多张图像。
The paper stated that the SealNet software could be a valuable tool in the developing field of "conservation technology" - technology aimed at saving and protecting wild animals.
该论文称，SealNet软件可能是发展中的“保护技术”（旨在拯救和保护野生动物的技术）领域的一个有价值的工具。
Harbor seals are a conservation success story in the U.S.
在美国，港海豹是一种被保护成功的动物。
More than 100 years ago, the animals were once widely killed.
100多年前，这种动物曾被广泛捕杀。
But the Marine Mammal Protection Act, which turned 50 in October, gave them new protections — and populations began to come back.
但在10月满50周年的《海洋哺乳动物保护法》为它们提供了新的保护措施，从而使得它们的数量开始回升。
Seals and other ocean mammals have long been studied using satellite technology.
长期以来，人们一直使用卫星技术研究海豹等海洋哺乳动物。
Using artificial intelligence to study them is a way to bring conservation into the 21st century, said Jason Holmberg of Wild Me.
Wild Me的杰森·霍姆伯格说，使用人工智能研究它们是将保护工作带入21世纪的一种方式。
The Oregon-based company works to bring machine learning to biologists.
这家总部位于俄勒冈州的公司致力于将机器学习带给生物学家。
Wild Me is developing a possible partnership with SealNet.
Wild Me正在与SealNet建立可能的合作伙伴关系。
Harbor seals are now common in the waters off the coast of the Northeastern United States.
港海豹目前在美国东北部沿海水域很常见。
Other seal species, however, remain at risk.
然而，其他海豹物种仍然处于危险之中。
The Mediterranean monk seal is thought to be the world's most at-risk seal with only a few hundred animals remaining.
地中海僧海豹被认为是世界上最濒危的海豹，仅存数百只。
Facial recognition technology could provide valuable data, said Michelle Berger, an associate scientist at the Shaw Institute in Maine.
缅因州邵氏研究所的副科学家米歇尔·伯杰说，面部识别技术可以提供有价值的数据。
Berger was not involved in the SealNet research.
伯杰没有参与SealNet研究。
"Once the system is perfected I can picture lots of interesting" environmental uses for it, Berger said.
伯杰说，“一旦这个系统完善，我就可以想象出它的许多有趣的环境用途。”
"If they could recognize seals, and recognize them from year to year, that would give us lots of information about movement, how much they move from site to site."
“如果它们能够识别海豹，并年复一年地识别它们，这将为我们提供大量关于海豹活动的信息，包括它们从一个地点移动到另一个地点的数据。”
The Colgate researchers are also working with FruitPunch, a Dutch artificial intelligence company, to improve some parts of SealNet to help more scientists use it, said Tjomme Dooper, FruitPunch's head of partnerships and growth.
科尔盖特大学研究人员还在与荷兰人工智能公司FruitPunch合作改进SealNet的某些部分，以帮助更多科学家使用它，FruitPunch的合作发展部主管Tjomme Dooper说。
That would open new opportunities to study the animals and help protect them, he said.
他说，这将为研究这些动物并帮助保护它们提供新的可能性。
"What this does is help the biologists study the behavior of seals, and also population dynamics," Dooper said.
Dooper说：“这有助于生物学家研究海豹的行为以及种群动态。”
He added that harbor seals give important information about the environment around them.
他还说，港海豹提供了有关它们周围环境的重要信息。
I'm John Russell.
约翰·拉塞尔为您播报。
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