Together with the Swedish University of Agricultural Sciences, Rewilding Europe and WWF Spain, FruitPunch AI announces the new AI for European Wildlife Challenge! 🐺🦌
For many ecosystems across the continent, balance requires human intervention. Whether it is the reintroduction of native species, the elimination of invasive species, mitigating human-wildlife conflict, or balancing predator and prey populations, it takes work to help wildlife thrive.
For conservationists to take effective measures, it is crucial to monitor the population dynamics of an ecosystem. Camera traps can help in doing so. The amount of data they generate however is quickly overwhelming. That’s why we need to automatically detect and identify animals on camera trap data.
In this Challenge we will build computer vision models to identify different species of European wildlife to improve population monitoring.
We are looking for people that want to learn more about computer vision or just want to show off their skills for a good cause 😉
You can expect to be working with:
The Challenge takes 10 weeks. By joining for 8h/w, it's a great opportunity to
- get started with ML in the Wildlife domain
- get your hands dirty with real datasets (~1M images), working for real stakeholders
- learn from enthusiasts and experts from all over the globe, both peer 2 peer and in Masterclasses
- build a network in AI for conservation
This is the first in a series of camera trap Challenges, where our ultimate goal is to build a general model architecture that can quickly be adapted to specific species & locations with relatively limited training sets.
Everyone from biologist to computer scientist can join as long as you have basic knowledge of Python programming and machine learning.
You can apply straight away through our platform:
Learn more about FruitPunch AI