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The iWildCam 2018 Challenge Dataset

Beery, Sara and Mac Aodha, Oisin and Van Horn, Grant and Perona, Pietro (2019) The iWildCam 2018 Challenge Dataset. . (Unpublished)

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Camera traps are a valuable tool for studying biodiversity, but research using this data is limited by the speed of human annotation. With the vast amounts of data now available it is imperative that we develop automatic solutions for annotating camera trap data in order to allow this research to scale. A promising approach is based on deep networks trained on human-annotated images. We provide a challenge dataset to explore whether such solutions generalize to novel locations, since systems that are trained once and may be deployed to operate automatically in new locations would be most useful.

Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription Paper
Beery, Sara0000-0002-2544-1844
Mac Aodha, Oisin0000-0002-5787-5073
Perona, Pietro0000-0002-7583-5809
Additional Information:We would like to thank the USGS and NPS for providing us with data. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship Program under Grant No. 1745301. 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.
Funding AgencyGrant Number
NSF Graduate Research FellowshipDGE-1745301
Record Number:CaltechAUTHORS:20200526-135628220
Persistent URL:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:103464
Deposited By: Tony Diaz
Deposited On:26 May 2020 21:34
Last Modified:20 Aug 2020 21:00

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