TECHNOLOGY
Scientists have developed a new technique based on artificial intelligence (AI) to count craters on the moon. "When it comes to counting craters on the moon, it's a pretty archaic method," said Mohamad Ali-Dib from the University of Toronto, Scarborough in Canada. "Basically we need to manually look at an image, locate and count the craters and then calculate how large they are based off the size of the image. Here we've developed a technique from artificial intelligence that can automate this entire process that saves significant time and effort," Ali-Dib said.
Scientists have developed a new technique based on artificial intelligence (AI) to count craters on the moon. "When it comes to counting craters on the moon, it's a pretty archaic method," said Mohamad Ali-Dib from the University of Toronto, Scarborough in Canada. "Basically we need to manually look at an image, locate and count the craters and then calculate how large they are based off the size of the image. Here we've developed a technique from artificial intelligence that can automate this entire process that saves significant time and effort," Ali-Dib said.
Researchers have tried in the past to develop algorithms that could identify and count lunar craters but when they were used on new, previously unseen patches of craters they tended to perform poorly.
By comparison, the technique developed by Ali-Dib and his colleagues can generalise very well to unseen lunar patches, and even other cratered bodies like Mercury. "It's the first time we have an algorithm that can detect craters really well for not only parts of the moon, but also areas of Mercury," said Ali-Dib.
In order to determine its accuracy, the researchers first trained the neural network on a large data set covering two thirds of the moon, and then tested their trained network on the remaining third of the moon. It worked so well that it was able to identify twice as many craters as traditional manual counting. In fact, it was able to identify about 6,000 previously unidentified craters on the moon.
According to a research published in the journal Icarus, the technique itself relies on a convolutional neural network, a class of machine learning algorithms that has been successfully used for computer vision to power robots and even self-driving cars. The data used by the algorithms was taken from elevation maps gathered from orbiting satellites. "Tens of thousands of unidentified small craters are on the moon, and it's unrealistic for humans to efficiently characterise them all by eye," said Ari Silburt from the University of Toronto, Scarborough.
"There's real potential for machines to help identify these small craters and reveal undiscovered clues about the formation of our solar system," Silburt said. Knowing the size and location of craters on bodies like the moon is important because it offers a window into the history of our solar system.
By studying impact craters of all shapes, sizes and ages, researchers can better understand the distribution of material and the physics that occurred in the early stages of our solar system, Ali-Dib said.
Since the moon lacks an atmosphere, plate tectonics and water, there is little erosion and as a result some impact craters as old as four billion years are visible. The ages of large craters can also be determined by counting how many small craters are found inside it.
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