Can you spot the lone dugong in the image above? Look closer. Closer still no? Try this larger version. Dedicate up? Here it is . Now do that with 45,000 more, and youll have a general notion of the population of these imperiled critters. If that sounds tedious, then perhaps you, like researchers at Murdoch University, would prefer to delegate the duty to a specially-trained computer.

Amanda Hodgson, of the schools Cetacean Research Unit, has been using UAVs to capture images of marine animals for years, but the data piles up fast, and there are only so many grad students.

This ones a little easier.

Hodgson worked with computer scientist Frederic Maire, of the Queensland University of Technology, to automate the process.

They developed a machine learningsystem on imagery where the sea cows had already been tagged, allowing it to look at fresh photographs and spot them with about 80 percent accuracy. The success rate should improve, and at any rate its good enough to give a ballpark measure and indicate images that need to be scrutinized more closely.

The one below, for example, may need to be double-checked, since there are so many animals in it and the shadows may fool the organizations of the system into counting a few twice 😛 TAGEND

With some tweaks, the organizations of the system could also be convinced to watch for whales, dolphins, boats, and other common features of the coast that could stand to be quantified.

Just one more style that machine learning and computer vision are helping out scientists and others across the globe.

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