Early Forest Fire Detection
Democratize open and low-tech solutions for fighting wildfires, for the benefit of the ecosystems and the citizens.
Open Technology for wildlife + planet
Building open source AI tools that help conservation scientists monitor wildlife, detect threats, and protect ecosystems.
👨🏻💻 Featured Projects
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Wild Salmon Migration Monitoring
The project monitors wild salmon migration to ensure the number passing through meets state regulations, addressing threats from human activities like fisheries and dams.
Forest Elephants Passive Acoustic Monitoring
Conservation efforts struggle to monitor forest elephants in dense rainforests, with acoustic monitoring providing a promising solution via accurate, user-friendly detection systems that aid in population monitoring and anti-poaching efforts while mitigating human-elephant conflicts.
Monitoring Smolt Salmon Migration with Sonar
An innovative use of sonar imagery to monitor and analyze the migration patterns of smolt salmon as they journey from freshwater to the ocean
Wadden Sea Seal Monitoring
Automated seal population monitoring system using AI to count, classify, and identify individual seals from aerial imagery in the Wadden Sea.
Biowatch: Camera Trap Data, Visualized
A free, open-source desktop application for visualizing camera trap data to support conservation efforts.
😇 Looking for Funding
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Snow Leopard Monitoring
Non-invasive snow leopard monitoring using computer vision analysis of camera trap photos to identify individual animals.
Bird Flu Monitoring
Utilize drones for precise monitoring of breeding seabird colonies by detection of live and dead adults and chicks to determine survival and reproduction and asses the impact of avian influenza.
Tropical Bat Call Detection and Classification
Transforming bat population monitoring in Cambodia through advanced bio-acoustic analysis driven by Machine Learning algorithms.
🤝 Our Partners
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Mateo Lostanlen
Co-founder and CEO - Pyronear
We absolutely love working with you. You are incredibly professional. They trained our latest model and achieved outstanding performance, setting a new benchmark. They also implemented the MLOps pipeline!
Will Atlas
Salmon Watershed Scientist - Wild Salmon Center
It has been an absolute pleasure working with you on SalmonVision. Your diverse skillset, ability to be forward thinking, and work with our team of collaborators was essential to the success of our project. We really couldn't have done it without you! I hope we can continue working together to improve and expand the tools offered by SalmonVision over the coming years.
Yohan Runhaar
CTO - ReefSupport
I am very excited for what is ahead, there is so much potential in the work that's been done. Your hard work and passion have really shone through!
Thijs Suijten
Co-founder & CTO - HackThePlanet
They really helped us by training a YOLOv8 model for our system to prevent human-bear-conflicts. He thinks along well, knows what he is talking about and is a nice person to work with!
Melanie Clapham
Director & Conservation Scientist - The BearID Project
There is definitely a want and need from the conservation community to work with people like you, with your expertise, as the technical side to this type of development is often the barrier.
📚 Read Latest Posts
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Racing Models, Not Opinions: How We Ran Wildfire ML R&D for Pyronear
How a literature survey, self-contained experiments, and a shared leaderboard turned 28 research papers into a production smoke verifier with 4x fewer false alarms.
Smoke Is a Behavior: Inside Pyronear's Temporal Wildfire Detection Model
How the temporal smoke verifier works, step by step — detection boxes become tubes, stabilized crops make motion legible, and a vision transformer plus a tiny temporal head learn that smoke grows and drifts.
Volunteering at Wildlife Rescue Centers
Our experiences at various Wildlife Rescue Centers