Google-developed AI model SpeciesNet is being used to identify animals in camera trap images, giving researchers and conservation teams a faster way to sort large wildlife datasets. The model can classify nearly 2,500 animal categories and was trained using 65M labelled images provided by conservation partners.
Camera traps are widely used by homeowners, parks managers and research groups, but large projects can produce thousands or even millions of images that would take decades to identify manually. SpeciesNet is intended to help process those images at scale.
Originally part of the online platform Wildlife Insights, SpeciesNet was released a year ago as an open-source tool for others to download, adapt and refine. Over the past 12 months, research groups around the world have used it to spot pumas and ocelots in Colombia, elk and black bears in Idaho, cassowaries and musky rat-kangaroos in Australia, and lions and elephants in Tanzania’s Serengeti National Park.
The model is part of Google Earth AI, described as a collection of geospatial tools, datasets and AI models for deep planetary intelligence. Google says Earth AI is designed to help communities and nonprofits address pressing needs on the planet.
Source: research.google.
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