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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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Video: Discover the SMART Approach

The SMART Partnership
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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Wildlife Crime Tech Challenge Accelerator Bootcamp

Sophie Maxwell
Earlier this month, the 16 prize winners of the Wildlife Crime Tech Challenge were called to Washington D.C. for an Accelerator Boot Camp. Sophie Maxwell, a member of the prize winning team from the Zoological Society...

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Computer Vision to Identify Individual Animals

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....

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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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TEAM Network and Wildlife Insights

Eric Fegraus
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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ContentMine: Mining Helpful Facts for Conservation

Jenny Molloy
Thousands of papers and reports about flora and fauna are published each year. While peer-reviewed published information is vitally important to conservation organisations, the ever-increasing mountain of information...

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Introductions

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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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

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: [email protected]

 

Cheers,

Jason

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Google Releases Tensor Flow

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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"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.

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.

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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Cheap Space, DIY Imaging and Big Data

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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Technology for Traceability

Daniel Brizuela
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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From Data Collection to Decisions

Tim Wilkinson
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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