A consumer-grade drone can take photos of trees from above that are good enough to train a deep-learning algorithm to tell different species apart.
Details: The team behind the project flew drone over a forest in Kyoto, Japan, to take photos and then divided some of them into seven categories: six types of trees and one called “others,” for images that captured bare land or buildings.
Results: After some fiddling, the algorithm (which was on an earth-bound computer) achieved 89 percent accuracy overall.
Why it matters: Forest surveys typically use expensive systems outfitted with lidar or specialized cameras. This commercially available setup could be a cheap way to automate tree surveys, and the algorithm could be retrained to aid in disaster response, check pipelines for leaks, or help with other monitoring efforts that need to quickly cover a large area.
Geoffrey Hinton tells us why he’s now scared of the tech he helped build
“I have suddenly switched my views on whether these things are going to be more intelligent than us.”
ChatGPT is going to change education, not destroy it
The narrative around cheating students doesn’t tell the whole story. Meet the teachers who think generative AI could actually make learning better.
Deep learning pioneer Geoffrey Hinton has quit Google
Hinton will be speaking at EmTech Digital on Wednesday.
We are hurtling toward a glitchy, spammy, scammy, AI-powered internet
Large language models are full of security vulnerabilities, yet they’re being embedded into tech products on a vast scale.
Get the latest updates from
MIT Technology Review
Discover special offers, top stories, upcoming events, and more.