One way researchers discover "new" craters on Mars is to analyze images taken from NASA satellites that are pointed at the surface of the Red Planet. Researchers will look at a collection of images spanning over various time frames, then compare images of the surface to each other. If a new crater appears between an image taken on A date and an image taken B date, then researchers can estimate that an impact must have occurred sometime between the dates of the images taken. To analyze one image, a researcher will spend about 40 minutes. As humans tend to do, we have offloaded the process to technology that can complete the task much more efficiently, freeing up time for researchers to work on other tasks.

One of the biggest challenges in astronomy is also the most obvious: space is big, and it takes a long time to look at it all. This is why artificial intelligence has been such a boon to this science. It turns out that the same machine vision tools developed for tasks like guiding self-driving cars are also perfect for sorting through vast amounts of astronomical data. So, astronomers announced this month that they'd used AI to find 6,000 new craters on the Moon. The Moon is estimated to have hundreds of thousands of craters, mostly caused by impacts with asteroids and meteors.

Despite vast developments in technology over the last few decades, our method for counting craters on the Moon hasn't advanced much, with the human eye still being heavily relied on for identification. In an effort to eliminate the monotony of tracking lunar cavities and basins manually, a group of researchers at the University of Toronto Scarborough came up with an innovative technique that resulted in the discovery of 6,000 new craters. "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," said Mohamad Ali-Dib, a postdoctoral fellow at University of Toronto's Centre for Planetary Sciences and co-developer of the technology, in a news release. The method utilizes a convolutional neural network, the same machine learning algorithm used for computer vision and self-driving cars. The research team used data from elevation maps, collected by orbiting satellites, to train the algorithm on an area that covers two-thirds of the Moon's surface.

Researchers first trained the neural network on 90,000 images that covered two-thirds of the moon's surface before testing its ability to detect craters on the remaining third portion of the data. Officials discovered that their network was able to categorize craters larger than 5 kilometers, ZME Science reported. "When it comes to counting craters on the moon, it's a pretty archaic method," Mohamad Ali-Dib, a postdoctoral researcher at the Centre for Planetary Sciences at University of Toronto Scarborough, said in a university press release. "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," he added.

Scientists have mapped 6,000 new craters on the Moon with the help of a newly developed technique based on artificial intelligence (AI). "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.

A new artificial intelligence (AI)-based lunar mapping technology has accurately mapped over 6,000 new craters on Earth's moon in just hours, the media reported. The moon is dotted with a vast number of craters, some billions of years old. Using the new lunar mapping technique, the technology successfully counted new pockmarks on the moon -- some 6,000 of them -- through available datasets from previous lunar observation information, Tech Times reported. "Basically, we need to manually look at an image, locate and count the craters and then calculate how large they are based on the size of the image," Mohamad Ali-Dib, from the Centre for Planetary Sciences at University of Toronto Scarborough, Canada, was quoted as saying. For the study, published in the journal Icarus, the team first trained the convolutional neural network on a dataset covering two-thirds of the moon.

Mankind's first home away from Earth may soon be located, thanks to the findings of an AI that can scour the moon to find new craters. Experts say that a future lunar base could be set up in one of the giant impact sites, protecting colonists from dangerous solar radiation. Now, a piece of computer software has been developed that was able to uncover almost 7,000 previously undiscovered craters in a matter of hours. The finding was made by a team of researchers led by Ari Silburt at Penn State University and Mohamad Ali-Dib at the University of Toronto. They fed 90,000 images of the moon's surface into an artificial neural network (ANN).