This is the best summary I could come up with:

Researchers in New Brunswick are developing a new approach to tackling Canada’s growing threat of wildfires: teaching artificial intelligence to find them faster.

A team of engineers at the Université de Moncton is fine-tuning an algorithm that works with satellite and drone images to detect fires more accurately than humans.

Moulay Akhloufi, a computer science professor and head of the Perception, Robotics and Intelligent Machines Laboratory, said it can help spot signs of a fire the human eye would miss.

Inside the Moncton lab, researchers are looking at how machine learning can help with both early detection of fires and modelling possible spread.

The algorithm for spotting fires quickly analyzes data from different sources, including sensors on the ground and images from drones and satellites.

“Whether using drones or UAVs [unmanned aerial vehicles], or small satellites or ground-based cameras, they basically allow you to have a more hands-off approach when it comes to fire monitoring,” said Morgan Crowley, a forest fire research scientist with Natural Resources Canada who is part of the team working on the mission.

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