With new technologies revolutionizing data collection, wildlife researchers are becoming increasingly able to collect data at much higher volumes than ever before. Now we are facing the challenges of putting this information to use, bringing the science of big data into the conservation arena. With the help of machine learning tools, this area holds immense potential for conservation practices. The applications range from online trafficking alerts to species-specific early warning systems to efficient movement and biodiversity monitoring and beyond.
However, the process of building effective machine learning tools depends upon large amounts of standardized training data, and conservationists currently lack an established system for standardization. How to best develop such a system and incentivize data sharing are questions at the forefront of this work. There are currently multiple AI-based conservation initiatives, including Wildlife Insights and WildBook, that are pioneering applications on this front.
This group is the perfect place to ask all your AI-related questions, no matter your skill level or previous familiarity! You'll find resources, meet other members with similar questions and experts who can answer them, and engage in exciting collaborative opportunities together.
Just getting started with AI in conservation? Check out our introduction tutorial, How Do I Train My First Machine Learning Model? with Daniel Situnayake, and our Virtual Meetup on Big Data. If you're coming from the more technical side of AI/ML, Sara Beery runs an AI for Conservation slack channel that might be of interest. Message her for an invite.
Header Image: Dr Claire Burke / @CBurkeSci
Explore the Basics: AI
Understanding the possibilities for incorporating new technology into your work can feel overwhelming. With so many tools available, so many resources to keep up with, and so many innovative projects happening around the world and in our community, it's easy to lose sight of how and why these new technologies matter, and how they can be practically applied to your projects.
Machine learning has huge potential in conservation tech, and its applications are growing every day! But the tradeoff of that potential is a big learning curve - or so it seems to those starting out with this powerful tool!
To help you explore the potential of AI (and prepare for some of our upcoming AI-themed events!), we've compiled simple, key resources, conversations, and videos to highlight the possibilities:
Three Resources for Beginners:
- Everything I know about Machine Learning and Camera Traps, Dan Morris | Resource library, camera traps, machine learning
- Using Computer Vision to Protect Endangered Species, Kasim Rafiq | Machine learning, data analysis, big cats
- Resource: WildID | WildID
Three Forum Threads for Beginners:
- I made an open-source tool to help you sort camera trap images | Petar Gyurov, Camera Traps
- Batch / Automated Cloud Processing | Chris Nicolas, Acoustic Monitoring
- Looking for help with camera trapping for Jaguars: Software for species ID and database building | Carmina Gutierrez, AI for Conservation
Three Tutorials for Beginners:
- How do I get started using machine learning for my camera traps? | Sara Beery, Tech Tutors
- How do I train my first machine learning model? | Daniel Situnayake, Tech Tutors
- Big Data in Conservation | Dave Thau, Dan Morris, Sarah Davidson, Virtual Meetups
Want to know more about AI, or have your specific machine learning questions answered by experts in the WILDLABS community? Make sure you join the conversation in our AI for Conservation group!
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DeepFaune: a software for AI-based identification of mammals in camera-trap pictures and videos
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25 October 2023 8:57am
That's a very interesting question and use case (I'm not from deepfaune). I'm playing with this at the moment and intend to integrate it into my other security software that can capture and send video alerts. I should have this working within a few weeks I think.
The structure of that software is that it is two stage, the first stage identifies that there is an animal and it's bounding box and then there's a classification stage. I intend to merge the two stages so that it behaves like a yolo model so that the output is bounding boxes as well as what type of animal it is.
However, my security software can cascade models. So if you were able to train a single stage classifier that identifies your particular bears, then you could cascade all of these models in my software to generate an alert with a video saying which bear it was.
4 November 2023 4:51am
Hi @GermanFore ,
I work with the BearID Project on individual identification of brown bears from faces. More recently we worked on face detection across all bear species and ran some tests with identifying Andean bears. You can find details in the paper I linked below. We plan to do more work with Andean bears in 2024.
I would love to connect with you. I'll send you a message with my email address.
Regards,
Ed
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24 October 2023 8:46pm
Hello to all, new to this group. This is very exciting technology. can it work for ID of individual animals? we are interested in Ai for identifying individual jaguars (spots) and andean Bears (face characteristics). Any recommendation? contact? thanks!
German