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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 traps 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. The AI For Conservation group is intended to unite and inspire all WILDLABS community members—whether already involved in AI for conservation, or not—to understand how to use and/or directly contribute to open-source research and development efforts.

Group curators

Anna Vallery
Seabird biologist experienced in research and applied conservation. Dedicated to conducting and using innovative research to inform conservation decisions.
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Viktor Domazetoski
PhD student at University of Exeter & University of Queensland. Interested in researching AI and its responsible application to Ecology, Environmental Monitoring and Nature Conservation.
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event

Video: Discover the SMART Approach

The SMART Partnership

20 July 2016 12:00am

The Spatial Monitoring and Reporting Tool (SMART) Partnership combines a ranger-based data collection tool with capacity building and a suite of best practices aimed at helping protected area and wildlife managers...

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discussion

Computer Vision to Identify Individual Animals

Jason Holmberg

29 May 2016 4:52am

Here's a demo of the work we're doing to identify individual humpback whales (and other species) using computer vision and A.I. on the IBEIS.org project. https://www....

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Stephanie O'Donnell

6 June 2016 11:17am

Hi Jason, 

Thanks for sharing this demo, it's interesting to see the fluke id process in action. Is this part of the flukebook project? How do you see the project progressing - are there opportunities for people to get involved or challenges it would be helpful to get outside input on? 

Cheers,

Stephanie

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article

TEAM Network and Wildlife Insights

Eric Fegraus

28 April 2016 12:00am

Operating the largest tropical forest camera trap network globally, TEAM Network has accumulated over 2.6 million images. How can large datasets coupled with new techniques for data management and analysis provide...

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discussion

Introductions

David J Klein

10 December 2015 8:13pm

Welcome to the Machine and Deep Learning group! Here, we'll be discussing current and future uses of Deep Learning (DL) and more broadly Machine Learning (ML) for improving...

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David J Klein

10 December 2015 8:41pm

To start things off...

I'm David J Klein. My background is in deep learning, machine learning, neuroscience, neuromorphic computing, and signal processing. I've been doing the startup thing Silicon Valley for the last 11 years after being in academia for a while. I've worked on products ranging from speech recognition systems, to cloud-based deep learning platforms. These days, some use the blanket term "AI". 

For the last several years I've been developing software for Conservation Metrics which gives their analysists the ability to use deep learning to process large volumes of audio and image data from remote sensors in order to monitor population density changes of endangered species, detect collisions of birds and bats with infrastructure,  and find rare and elusive species. 

More broadly, I'm interested in integrating many disparate sensing domains from eDNA, to land-based sensors, to GIS data in order to provide tools to conservation scientists and ecologists that will enable them to develop a higher resolution understanding of the health of ecosysems around the globe and their response to positive or negative human interventions.

I'm looking forward to interacting with you all. Please let me know what other questions you have for me, and other ways I can help.

Regards,
David

Jason Holmberg

17 January 2016 9:08pm

Hi,

 

I am jason Holmberg from WildMe.org. I am one of the developers of Wildbook (wildbook.org), an open source data management platform for wildlife research. I'm using ML as part of the IBEIS.org project to boost and metascore multiple computer vision algorithms for individual humpback and sperm whales. David, I would love to speak offline if you have the time: jason@wildme.org.

 

Cheers,

Jason

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discussion

Google Releases Tensor Flow

Sophie Maxwell

18 November 2015 12:10am

Google have ignored all warnings from the Terminator and opened sourced their AI code. This has huge potential for use in conservation. How can we use it?

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Courtney Dunn

20 December 2015 7:05pm

"TensorFlow, you see, deals in a form of AI called deep learning. With deep learning, you teach systems to perform tasks such as recognizing images, identifying spoken words, and even understanding natural language by feeding data into vast neural networks. "

Would this be applicable to an acoustic monitoring network? For example. my research has shown tigers have unique, identifiable vocalizations down to the individual and sex. If this software is applied to my recording network for tigers, would it be able to automatically recognize and categorize these individuals?

For example: when it hears Tiger 108, it would know and then input that it heard Tiger 108 at a particular time and date.

Chavoux Luyt

11 January 2016 12:38pm

The catch will be (and for any neural network or AI type learning I would expect the same) the training phase. If you are able to tell the sounds apart or identify a specific sound as belonging to a certain individual, the AI should afterwards be able to automatically identify the critical factors needed to distinguish the voices of the individuals. But it will need enough input from each individual as well as the different vocalizations used by tigers. AFAIKT it will be able to do this automatically afterwards, but I am not sure if (a) you will get enough identifiable vocalisations and (b) with a wide enough range of typical tiger vocalisations for it to be really reliable. Training on zoo animals might work? I am also interested in this, but for jackals instead of tigers.

Jason Holmberg

11 January 2016 2:30pm

I'd like to suggest our open source package Wildbook (http://www.wildbook.org) as a base data management platfor for this. I agree with the above that there are a number of challenges around the vocalizations themselves, but having the identity information in a good database and data model is a great foundation. That's what we're doing for our computer vision/deep learning project at www.IBEIS.org.

 

Our non-profit WildMe.org is running both. Feel free to contact us with questions. We have played with time series matching (often used for speech recognition)...but actually for whale flukes. Would be happy to discuss potential for audio ID. 

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article

Cheap Space, DIY Imaging and Big Data

WILDLABS Admin

21 December 2015 12:00am

John Amos, President of SkyTruth, explores how remote sensing is being used in conservation today and the importance of sky-truthing. He examines the role that citizen scientists can play in increasing transparency in...

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article

Technology for Traceability

Daniel Brizuela and 1 more

26 November 2015 12:00am

Traceability (knowing where products come from and how they are made) is a foundational pre-cursor for many sustainability interventions. While many tools have been developed to offer high-level insight about the...

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article

From Data Collection to Decisions

TimWilkinson

6 November 2015 12:00am

The speed at which data travels from the point of collection to a format which is understandable and useful for decision makers can be of critical importance. In this case study, Tim Wilkinson discusses a powerful suite...

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