Scientists believe they have found a new use for facial recognition technology: saving large ocean animals known as seals.
科学家们相信他们发现了面部识别技术的新用途：拯救被称为海豹的大型海洋动物。
 
Researchers at Colgate University in the U.S. state of New York have developed SealNet. The system is a database of seal faces created by taking pictures of many harbor seals in Maine's Casco Bay.
科尔盖特大学的研究人员美国纽约州开发了SealNet。该系统是一个海豹面孔数据库，通过拍摄缅因州卡斯科湾的许多斑海豹照片创建。
 
The research team found the tool's accuracy in identifying the mammals was close to 100 percent.
研究团队发现该工具识别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. She is a biology professor at Colgate and a team member.
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，Krista Ingram 说。她是高露洁大学的生物学教授和团队成员。
 
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.
增加数据库以包括地中海僧海豹和夏威夷僧海豹等稀有物种可以帮助拯救这些物种，她说。
 
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，创建海豹面孔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......在海域周围移动的海洋哺乳动物很多并且很难在水中拍摄，我们需要能够识别个体。”
 
SealNet is designed to identify the face in a picture. It recognizes the seal's face based on information related to the eyes and nose shape, as it would a human. 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.
SealNet 旨在识别照片中的人脸。它根据与眼睛和鼻子形状相关的信息识别海豹的面部，就像识别人类一样。高露洁研究人员表示，一种名为 PrimNet 的类似工具用于灵长类动物，之前曾用于海豹，但 SealNet 表现更好。
 
 
The Colgate team published its findings last spring in Ecology and Evolution. They processed more than 1,700 images of more than 400 individual seals, the paper said.
高露洁团队去年春天在生态学和进化论上发表了他们的发现。该论文称，他们处理了 400 多只海豹的 1,700 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 软件可能成为“保护技术”发展领域的宝贵工具 - 旨在保护动物的技术拯救和保护野生动物。
 
Harbor seals are a conservation success story in the U.S. 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 began to come back.
海豹在美国是一个成功的保护故事。100 多年前，这些动物曾被广泛捕杀。但 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——数量开始回升。
 
Seals and other ocean mammals have long been studied using satellite technology. Using artificial intelligence to study them is a way to bring conservation into the 21st century, said Jason Holmberg of Wild Me. The Oregon-based company works to bring machine learning to biologists. Wild Me is developing a possible partnership with SealNet.
长期以来，人们一直在使用卫星技术研究海豹和其他海洋哺乳动物。 Wild Me 的 Jason Holmberg 说，使用人工智能研究它们是将保护带入 21 世纪的一种方式。这家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 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. Other seal species, however, remain at risk. The Mediterranean monk seal is thought to be the world's most at-risk seal with only a few hundred animals remaining.
斑海豹现在在美国东北部沿海水域很常见。然而，其他海豹物种仍处于危险之中。地中海僧海豹被认为是世界上最危险的海豹，仅存数百只。
 
Facial recognition technology could provide valuable data, said Michelle Berger, an associate scientist at the Shaw Institute in Maine. Berger was not involved in the SealNet research.
缅因州逸夫研究所的副科学家 Michelle Berger 说，面部识别技术可以提供有价值的数据。 Berger 没有参与 SealNet 研究。
 
"Once the system is perfected I can picture lots of interesting" environmental uses for it, Berger said. "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."
“一旦系统完善，我就可以想象出很多有趣的”环境用途，Berger 说。 “如果他们能认出海豹，并且年复一年地认出它们，那将为我们提供大量关于运动的信息，包括它们从一个地方到另一个地方的移动量。”
 
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.
FruitPunch 合作伙伴关系和发展主管 Tjomme Dooper 表示，高露洁研究人员还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。
 
That would open new opportunities to study the animals and help protect them, he said.
这将打开他说，这是研究这些动物并帮助保护它们的新机会。
 
"What this does is help the biologists study the behavior of seals, and also population dynamics," Dooper said. He added that harbor seals give important information about the environment around them.
“这有助于生物学家研究海豹的行为以及种群动态，”Dooper 说。他补充说，斑海豹提供有关它们周围环境的重要信息。