"Supporting biodiversity (amateur) scientists, natural history collection managers, and nature conservationists with automated species recognition"
The availability of large multimedia databases on plants, animals, and fossils, both specimens and observations of living organisms, forms a fantastic resource for creating automatic species identification software based on image recognition using deep learning and other forms of AI.
The AI Nature initiative creates species identification models based on images from naturalis history collections and observation platforms. User software has been developed to make these models accessible and easy to use for specific biodiversity work areas, i.e.:
- Biodiversity and nature research at both professional and amateur levels
- Management of natural history collections
- Nature management and conservation
- Nature education
The AI Nature initiative wants to implement deep-learning solutions for user communities within these work areas. It also wants to create technical solutions that encourage and help third parties to do the same.
This initiative started in 2018. Use cases in the first three biodiversity work areas have been finalized or are in the prototype stage. New initiatives have been started!
Automatically identifying new observations on the fly
Monitoring the decline of insect biodiversity
Focus on the rare, get more done in collections management
Tracking climate change impact by classifying snail shells