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Software, Data & Models used in "Identifying Animal Species in Camera Trap Images using Deep Learning and Citizen Science"

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Software, Data & Models used in "Identifying Animal Species in Camera Trap Images using Deep Learning and Citizen Science"

Published Date

2018-08-28

Author Contact

Willi, Marco
will5448@umn.edu

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Abstract

This dataset provides the software, the models, and other data used in "Identifying Animal Species in Camera Trap Images using Deep Learning and Citizen Science". This dataset contains the software to train convolutional neural networks, as well as all models trained for the study and code to apply them on new images. Additionally, data defining the conducted experiments are provided to ensure reproducibility.

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Referenced by

Willi M, Pitman R, Cardoso A, Locke C, Swanson A, Boyer A, Veldthuis M, Fortson L, Identifying Animal Species in Camera Trap Images using Deep Learning and Citizen Science, 2018, Methods in Ecology and Evolution
https://doi.org/10.1111/2041-210X.13099

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Funding information

This study was partially supported by the NSF under award IIS 1619177
The development of the Zooniverse platform was partially supported by a Global Impact Award from Google.
We also acknowledge support from STFC under grant ST/N003179/1.
EE was funded by the University of Oxford’s Hertford College Mortimer May fund.

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Willi, Marco; Pitman, Ross T; Cardoso, Anabelle W; Locke, Christina; Swanson, Alexandra; Boyer, Amy; Veldthuis, Marten; Fortson, Lucy. (2018). Software, Data & Models used in "Identifying Animal Species in Camera Trap Images using Deep Learning and Citizen Science". Retrieved from the Data Repository for the University of Minnesota (DRUM), https://doi.org/10.13020/D6P67B.

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