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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.
Vote for your favorite submissions that best demonstrate conservation impact, novel innovation/discovery, and strong storytelling of the work and the sector.
Camera trapping for insects is becoming a reality using advances in camera, AI, and autonomous systems technologies. This group discusses the latest advances, shares experiences, and offers a space for anyone interested in the technology, from beginners to experts.
WildLabs will soon launch a 'Funding and Finance' group. What would be your wish list for such a group? Would you be interested in co-managing or otherwise helping out?
Welcome to the official group forum for our virtual course, Build Your Own Data Logger. This is your space to engage with course instructors Akiba and Jacinta from Freaklabs, find help and resources for each module, collaborate and chat with your fellow course participants, and share your progress on your own Data Logger project!
Can conservation-based incentives promote the willingness of local
communities to coexist with wildlife? A case of Burunge Wildlife
Management Area, Northern Tanzania
Looking for a place to discuss camera trap troubleshooting, compare models, collaborate with members working with other technologies like machine learning and bioacoustics, or share and exchange data from your camera trap research? Get involved in our Camera Traps group! All are welcome whether you are new to camera trapping, have expertise from the field to share, or are curious about how your skill sets can help those working with camera traps.
Vote for your favorite submissions that best demonstrate conservation impact, novel innovation/discovery, and strong storytelling of the work and the sector.
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