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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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Bird Sounds Global web portal

A new web portal for annotating bird sounds has been opened called Bird Sounds Global (BSG). It is part of project LIFEPLAN, and its key objective is to develop global, automated software for bird sound identification.

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Really cool platform! Will definitely add it to our next update of the Conservation Tech Directory. Curious, could there be cross-platform integration with something like Xeno-...
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careers

Science Director, Vulcan

Vulcan
Are you passionate about making a meaningful impact on our community? Seattle-based Vulcan is looking to hire a science leader to support its work advising the Paul G. Allen Family Foundation.

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event

CV4Ecology Summer School

A three-week intensive summer school teaching Computer Vision Methods for Ecology, seeking to empower ecologists to accurately and efficiently analyze large image, audio, or video datasets using computer vision....

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article

WILDLABS Virtual Meetups Season Four: Tracking Progress

WILDLABS Team
This season, we’re bringing together leading engineers, conservationists, and academics to explore the future of technology in movement ecology and ask where exactly investment is needed to catapult this field forward....

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event

BirdCLEF 2022 Kaggle Challenge

The Cornell Lab of Ornithology
Join the BirdCLEF 2022 Kaggle challenge, where you’ll use your machine learning skills to identify bird species by sound. You'll develop a model that can process continuous audio data and then acoustically recognize the...

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article

Introducing the WILDLABS On the Edge Fellows

WILDLABS Team
We're proud to introduce the first WILDLABS On the Edge Fellows for 2022, Loretta Schindlerova and Meredith Palmer! Working alongside expert Edge Impulse mentors, these two fellows will use embedded machine learning to...

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article

Deep Learning for Marine Ecology and Conservation

arXiv (Journal)
This article provides a review of deep learning (predominantly ML) used in marine ecology and considerations for its future directions in conservation. In plain language, the authors provide a methodology for training...

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discussion

AI for Conservation Office Hours: are you interested?

Hi Wildlabbers! Let me introduce myself, I’m Lucas - I’ve just started interning at WILDLABS with a background in languages and Latin American Studies and I’m...

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Hi Wildlabbers! 

We're now going ahead with a small pilot of around ten 1:1 office hour sessions with Microsoft AI for Earth specialists. More details coming very soon.    

For the time being sign-ups are now closed, but thank you to everyone who has been interested. We will keep you updated on how the 1:1s go and whether there will be further sessions to sign up for later in the year. 

Cheers, 

Lucas

We've now wrapped our first run of AI for Conservation Office Hours and you can read my review of how it went and lessons learned here

Given the overall success of the programme, we're excited to announce that in early spring next year we will be coordinating a second round - so keep an eye out for further updates in the new year on the application and sign-up process. 

Also, we'd love to know whether you'd be interested in having a 1:1 so comment below and tell us what conservation tech challenge you would like to cover or how a session could help you in your conservation work. 

Many thanks, 

Lucas 

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community announcement

AI for Conservation Office Hours: 2021 Review

We've wrapped our first AI for Conservation Office Hours, a new programme where we set up 1:1 sessions with conservationists using or thinking about using AI so they could receive expert guidance from data scientists at...

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article

Low-cost underwater camera trapping and deep learning

Wake Forest University
This study breaks ground in outlining a methodology for a system of low-cost, long-term camera traps (Dispersed Environment Acquatic Cameras) that can be deployed over large spatial scales in remote marine environments...

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article

The race to save California's rarest butterflies

BBC
In pursuit of saving the Monarch butterflies, Carlo Mondavi- pioneer of the Monarch challenge- was inspired to develop the world's first fully electric smart tractor tractor with co-founder and Chief Executive, Praveen...

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article

Environmental Data Justice

Joycelyn Longdon
This research article explores the challenges of achieving environmental data justice, with the continued advancement in technology and growth in available data. The author emphasises the necessity to prioritise ...

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article

Caiman: Images as Sources of Intelligence

Sensing Clues Foundation
CAIMAN is a product from the Sensing Clues Foundation that automatically classifies animals on images from camera traps. It aims to be available by the end of 2021, contact the Sensing Clues team for more details. This...

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