Aerial Wildlife Detection
AIDE: Annotation Interface for Data-driven Ecology – Tools for detecting wildlife in aerial images using active learning
Accelerating Biodiversity Surveys with AI
Tools
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Pytorch-wildlife
At the core of our mission is the desire to create a harmonious space where conservation scientists from all over the globe can unite. Where they’re able to share, grow, use datasets and deep learning architectures for wildlife conservation. We’ve…
Microsoft AI for Earth Species Classification API
This project contains the training code for the Microsoft AI for Earth Species Classification API, along with the code for our API demo page (opens in new tab). This API classifies handheld photos of around 5000 plant and animal species. There…
Multi-species Bioacoustic Classification
Multi-species bioacoustic classification using deep learning algorithms. With audio recordings collected from rainforests in Puerto Rico, we build a deep learning model that combines transfer learning and pseudo-labeling as a data augmentation technique to: 1) train a deep convolutional neural…
Beluga Sounds
Using machine learning to detect beluga whale calls in hydrophone recordings. Of the five populations of beluga whales in Alaska, the Cook Inlet population is the smallest and has declined by about seventy-five percent since 1979. Listed as an endangered…
Arctic Seals
A deep learning project in cooperation with the NOAA Marine Mammal Lab to detect & classify arctic seals in aerial imagery to understand how they’re adapting to a changing world.