Tjomme Dooper
- @Tjomme
- | He/Him
As apex predators, eagles are key indicators of ecosystem health. Accurate monitoring of their populations can therefore serve as a warning system for an entire ecosystem.
Traditional methods of monitoring eagles often involve capturing, tagging, or otherwise disturbing the birds. Photo-based monitoring can provide a non-invasive alternative, minimizing disturbance to the eagles and reducing potential negative impacts on their behavior and well-being. But it's much easier to take a picture than to identify what's on it. Digging through thousands of images and determining the species, age and sex of birds is an arduous task. Luckily, machine learning can lend a helping hand.
In the AI for Eagles Challenge, by FruitPunch AI 50 AI enthusiasts and experts from all over the globe will be training classifiers to recognize golden and white-tailed eagles in flight and classify them into age groups.
We are looking for data scientists & ML engineers. Previous work with computer vision and model deployment would be of great benefit, but it's not a requirement. The Challenge includes a masterclass on ecology and computer vision to bring you up to speed.
Anyone that joins us for 8h/w can
- spread their wings in ML for the Wildlife domain
- dig their claws into real data, working for stakeholders in conservation
- learn from a flight of AI enthusiasts and experts from all over the globe
- expand their network to soar in AI for conservation
Learn more about FruitPunch AI
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