Improving the accessibility and transferability of machine learning algorithms for identification of animals in camera trap images: MLWIC2
M. A. Tabak, M. S. Norouzzadeh, D. W. Wolfson, E. J. Newton, R. K. Boughton, J. S. Ivan, E. A. Odell, E. S. Newkirk, R. Y. Conrey, J. Stenglein, F. Iannarilli, J. Erb, R. K. Brook, A. J. Davis, J. Lewis, , R. S. Miller
This paper develops two deep learning models for camera trap image classification, achieving high accuracy and transferability across locations, and provides an accessible R package for biologists.
bioRxiv · Mar 18, 2020Ecology