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<p>Camera trap wildlife surveys can generate vast amounts of imagery. A key problem in the wildlife ecology field is that vast amounts of time is spent reviewing this imagery to identify the species detected. Valuable resources are wasted, and the scale of studies is limited by this review process. The use of computer software capable of extracting false positives, automatically identifying animals detected and sorting imagery could greatly increase efficiency. AI has been demonstrated as an effective option for automatically identifying species from camera trap imagery. Currently available code bases are inaccessible to the majority of users; requiring high-performance computers, advanced software engineering skills and, often, high-bandwidth internet connections to access cloud services. The <em>ClassifyMe</em> software tool is designed to address this gap and provides users the opportunity to utilise state-of-the-art image recognition algorithms without the need for specialised computer programming skills. <em>ClassifyMe</em> is IDEAL for field researchers, allowing users to sweep through camera trap imagery using field computers instead of office-based workstations.</p>
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Our fourth and final meetup in Season 4 explored the future of movement ecology, including tools that could change the game and questions we might not yet have thought to ask. On June 8, we heard short talks from leading experts Christian Rutz, Ran Nathan, Martin Wikelski, and Tanya Berger-Wolf, followed by open discussion and community exchange.
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Erika Barthelmess's Content
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Hi folks: I'm looking for creative ideas for storing camera traps when they aren't in the field. I've got drawers in the lab, but the cameras become a bit of a tangled mess. Just...
02 June 2022
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