Title
Software, Data & Models used in "Identifying Animal Species in Camera Trap Images using Deep Learning and Citizen Science"
Published Date
2018-08-28
Authors
Group
University of Minnesota - School of Physics and Astronomy
University of Minnesota - Data Science MS program
Author Contact
Willi, Marco (will5448@umn.edu)
Type
Dataset
Programming Software Code
Statistical Computing Software Code
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.
Funding information
Sponsorship:
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.
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
Related to
Camera Trap Images used in "Identifying Animal Species in Camera Trap Images using Deep Learning and Citizen Science"
License
CC0 1.0 Universal Public Domain Dedication
Suggested Citation
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,
https://doi.org/10.13020/D6P67B.