Add SSHRC to acknowledgement, description to yaml
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README.md
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@@ -3,6 +3,7 @@ license: cc0-1.0
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language:
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- en
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pretty_name: The Wilds Drones
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task_categories:
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- image-classification
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- object-detection
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## Acknowledgements
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This project is supported by
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[Award # 2112606](https://www.nsf.gov/awardsearch/showAward?AWD_ID=2112606), Intelligent
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Cyberinfrastructure with Computational Learning in the Environment (ICICLE), and by the [Imageomics Institute](https://imageomics.org),
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which is funded by the US National Science Foundation's Harnessing the Data Revolution (HDR) program under
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[Award #2118240](https://www.nsf.gov/awardsearch/showAward?AWD_ID=2118240)
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(Imageomics: A New Frontier of Biological Information Powered by Knowledge-Guided Machine Learning).
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This work is also supported by the AI and Biodiversity Change (ABC) Global Center.
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The ABC Global Center is funded by the US National Science Foundation under [Award No. 2330423](https://www.nsf.gov/awardsearch/showAward?AWD_ID=2330423&HistoricalAwards=false)
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and the Natural Sciences and Engineering Research Council of Canada under [Award No. 585136](https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=782440).
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Any opinions, findings
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and do not necessarily reflect the views of the National Science Foundation or the Natural Sciences and
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Engineering Research Council of Canada.
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Special thanks to Dan Beetem and [The Wilds](https://www.thewilds.org/) in Ohio for providing access to deployment sites
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and supporting this wildlife monitoring research. We thank the Columbus Zoo Aquarium for their support in facilitating
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language:
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- en
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pretty_name: The Wilds Drones
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description: "Drone mission data collected at The Wilds safari park in Ohio during Summer 2025. Manual drone flights captured video footage of specific sites at The Wilds to support ecological monitoring, animal behavior analysis, and aerial object detection modeling."
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task_categories:
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- image-classification
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- object-detection
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## Acknowledgements
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This project is supported by the [AI Institute for Intelligent Cyberinfrastructure with Computational Learning in the Environment (ICICLE)](https://icicle.osu.edu/), which is funded by the US National Science Foundation under [Award #2112606](https://www.nsf.gov/awardsearch/showAward?AWD_ID=2112606), and by the [Imageomics Institute](https://imageomics.org),
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which is funded by the US National Science Foundation's Harnessing the Data Revolution (HDR) program under
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[Award #2118240](https://www.nsf.gov/awardsearch/showAward?AWD_ID=2118240)
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(Imageomics: A New Frontier of Biological Information Powered by Knowledge-Guided Machine Learning).
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This work is also supported by the AI and Biodiversity Change (ABC) Global Center.
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The ABC Global Center is funded by the US National Science Foundation under [Award No. 2330423](https://www.nsf.gov/awardsearch/showAward?AWD_ID=2330423&HistoricalAwards=false)
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and the Natural Sciences and Engineering Research Council of Canada under [Award No. 585136](https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=782440).
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This dataset draws on research supported by the Social Sciences and Humanities Research Council.
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Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation, Natural Sciences and Engineering Research Council of Canada, or Social Sciences and Humanities Research Council.
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Special thanks to Dan Beetem and [The Wilds](https://www.thewilds.org/) in Ohio for providing access to deployment sites
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and supporting this wildlife monitoring research. We thank the Columbus Zoo Aquarium for their support in facilitating
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