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AI for Conservation / Feed

Artificial intelligence is increasingly being used in the field to analyse information collected by wildlife conservationists, from camera trap and satellite images to audio recordings. AI can learn how to identify which photos out of thousands contain rare species; or pinpoint an animal call out of hours of field recordings - hugely reducing the manual labour required to collect vital conservation data.

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Celebrating World Oceans Day: Revitalizing the marine ecosystem with technology-driven engineered reefs to accelerate CO2 capture

As we celebrate World Oceans Day this month, we are reminded that addressing climate change will take more than any one organization. It will require companies, governments, NGOs and communities, all working together, with the aid of technology, to improve the efficiencies of our activities and operations and to reduce costs, waste and emissions. Such an example is IBM and The Reef Company recently joining forces signing a joint initiative agreement aimed at bolstering their ocean conservation endeavors.

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ISO Speakers for Emerging Technologies class.

Hi Everyone, Apologies for posting across multiple groups.  I'm teaching a new course @ Clark University next semester on emerging technologies for conservation. The course...

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Definitely interested! I'm in the ecoacoustics/acoustic monitoring space, working at Rainforest Connection and Arbimon.

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Happywhale: AI-Powered Whale Identification

Happywhale
In this Conservation Tech Showcase case study from Happywhale, you’ll learn about how AI tools are helping researchers and citizen scientists identify and protect humpback whales. 

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AI for Conservation Office Hours: 2023 Review

Jake Burton
We've now wrapped our 2023 AI for Conservation Office Hours, where we helped conservationists connect with AI experts to get tailored expert advice on AI and ML problems in their projects

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Crowdsourcing individual ID for pop dyn?

Hi! I'm trying to estimate abundance and survival in freshwater fish populations (trout and salmon) using AI for individual recognition from crowdsourced data: https://www.usgs....

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That sounds like a really neat project! Do fish get re-caught often enough that individual ID is useful? Is sample bias (more data from popular spots) an issue?

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Using computer vision to understand bee vision

Here's an innovative project from the Harvey Mudd College Bee Lab that could help us understand how bees view their environments, and thus better protect bee habitat. This project uses computer vision and drone imagery to replicate "bee vision" of flowers and how it differs from a human's view of the same habitat.

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Looking to contribute

Hi everybody 👋🏽,I'm a UX designer, and I design interfaces and improve user experiences/flows. I would love to contribute to conservation tech / climate tech, especially saving...

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Artificial Intelligence and Conservation with Lily Xu

WWF's recent Fuller Seminar Series on Artificial Intelligence and Conservation featured some familiar faces from the WILDLABS community, including our past Tech Tutor Lily Xu! Check out her presentation talking about AI-based causal reasoning and how it can be applied to conservation challenges.

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AI Animal Identification Models

Hi Everyone,I've recently joined WILDLABS and I'm getting to know the different groups. I hope I've selected the right ones for this discussion...I am interested in AI to identify...

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Thanks Dan, that is very helpful. No zebras here but I did see four deer wandering through the streets this morning. Quite wild at times here!

I am totally willing to try an image classifier if it reports multiple objects it identifies in a scene. I will give this a go.

I think 1 fps would be quite acceptable actually, and in some perspective actually advantageous in reducing how much data is getting logged.

I tried upgrading my existing object detector model to YOLOv8 following the links you sent, but I don't think it is possible to upgrade the model on the framework I'm using (ml5js) so I think I will have to try a different framework.

Thank you.

Hi David

It appears that you have been looking for existing models, however, most existing models are trained on either COCO or some other very generic dataset. So, if you want to identify just animals, you may be better off training your own model. It seems no one in this thread mentioned yet that it is possible to do transfer learning on existing models, which keeps most of the "visual part" of the model as is, but just changes the classification part so it can identify other things. This way you can take an existing model trained on COCO and in a fraction of the time it takes to train a full model, just retrain that for your animals.

Also have a look at your requirements for the inferencing stage. Some models take long in training but are superfast in inference and others are slow in both cases but very accurate, etc. If you want semi-realtime inferencing, you are probably looking at single shot detectors (SSD), and not RCNNs.

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