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-[x] The workflow allows collecting dense behavior data over large time and spatial scales
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-[x] Enables researchers to quickly annotate animals and behaviors of interest to generate dense behavior and annotation datasets
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-[x] The underlying light-weight network architecture and implementation can be employed for real-time animal detection and behavior classification in the wild
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-[x] The workflow is built around videos from consumer-grade single cameras enabling easy adoption for reserach and conservation in the field
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-[x] The workflow is built around videos from consumer-grade single cameras enabling easy adoption for research and conservation in the field
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We demonstrate the benefits of using this workflow on aerial video footage of zebras recorded at Mpala in Kenya. The [full annotated dataset](https://keeper.mpdl.mpg.de/d/a9822e000aff4b5391e1/) is freely available for the research community.
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@@ -51,7 +51,7 @@ A [Preprint outlining the framework](https://doi.org/10.1101/2023.07.31.551177)
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