Google Releases SpeciesNet, an AI Model Designed To Identify Wildlife

Google has open-sourced an AI model called SpeciesNet, which is designed to identify animal species by analyzing photos from camera traps. These traps, used by researchers globally to study wildlife populations, generate large volumes of data that are time-consuming to process. To address this, Google launched Wildlife Insights, a platform under its Google Earth Outreach philanthropy program, about six years ago. Wildlife Insights allows researchers to share, identify, and analyze wildlife images collaboratively, speeding up the data analysis process.

SpeciesNet, which powers many of Wildlife Insights' tools, was trained on over 65 million images from various organizations, including the Smithsonian Conservation Biology Institute and the Zoological Society of London. It can classify images into over 2,000 labels, covering animal species, taxa, and non-animal objects. SpeciesNet is available on GitHub under an Apache 2.0 license, allowing for commercial use with minimal restrictions.

Key takeaways

Google has open sourced an AI model called SpeciesNet to identify animal species from camera trap photos.
SpeciesNet is part of Google's Wildlife Insights initiative, which aims to help researchers analyze wildlife images more efficiently.
The model was trained on over 65 million images and can classify images into over 2,000 labels, including animal species and non-animal objects.
SpeciesNet is available on GitHub under an Apache 2.0 license, allowing for commercial use with minimal restrictions.

Google Releases SpeciesNet, an AI Model Designed To Identify Wildlife - Slashdot

Key takeaways

Discussion (0)