Accelerate your impact
AI for Earth APIs and applications give organizations the scale and flexibility to transform how they process data and generate valuable insights.
Species Classification API
The Species Classification API recognizes plants and animals in images, empowering citizen scientists and backyard enthusiasts with AI.Experience the demo
Citizen scientists make tremendous contributions to biodiversity research by taking and identifying photos of plants and animals. But the identification process remains dependent on human experts, creating a bottleneck in the scientific pipeline.
Using the Microsoft AI platform, specifically Deep Learning Virtual Machine, we trained a deep neural network to identify plant and animal species in images.
One or more images, each containing a plant or animal, are uploaded to the API. Over 5000 species are supported.
The API returns a list of candidate species, including both scientific and common names, along with a confidence value for each species on the list. A bounding box for each species is optionally included.
Species Classification API resources
The Species Classification API enables citizen scientists to track animal and plant species by utilizing AI and deep learning algorithms. View the API or request a key to advance your conservation efforts.
Explore more AI for Earth solutions using Azure and custom APIs.
Labeled Information Library of Alexandria: Biology and Conservation (LILA BC) accelerates innovation in machine learning for conservation by providing publicly available data sets.
Microsoft Azure and AI technologies enable farmers to improve yields, lower costs, and reduce the environmental impact of farming.
Computer vision models empower citizen scientists to collect data on species, their distributions, and the risks posed to their survival.
Microsoft boosted the speed and accuracy of Wild Me's Wildbook platform by migrating it to Azure, where computer vision identifies animals from crowdsourced images.
By hosting EarthRanger on Azure with multi-tenancy, Vulcan helps park rangers gather insights about their parks and fight poaching.
Machine learning workflows in Azure reduce processing time for data collected from remote sensors, producing faster, more reliable metrics from Conservation Metrics.
Using high-resolution satellite imagery and field data to train machine learning models on Azure, SilviaTerra is transforming how forests are managed.
Microsoft enabled PAWS to make sensitive poaching data available to conservationists by enabling a non-public API with Azure as the backend infrastructure.
Geo AI Data Science VM
Geo AI DSVM delivers geospatial analytics capabilities that improve the gathering, managing, and analyzing of geographic data in today’s IoT-driven world.
Robotic insect traps, paired with cloud-scale genomics and machine learning algorithms, enable biodiversity insights.
In addition to the specialized APIs and applications found here, Microsoft provides general APIs that might fit your needs.