Schneider, S., Taylor, G. W., & Kremer, S. C. (2020). Similarity Learning Networks for Animal Individual Re-Identification-Beyond the Capabilities of a Human Observer. Proceedings - 2020 IEEE Winter Conference on Applications of Computer Vision Workshops, WACVW 2020, 479, 44–52. https://doi.org/10.1109/WACVW50321.2020.9096925
Abstract

Deep learning has become the standard methodology to approach computer vision tasks when large amounts of labeled data are available. One area where traditional deep learning approaches fail to perform is one-shot learning tasks where a model must correctly classify a new category after seeing only one example. One such domain is animal re-identification, an application of computer vision which can be used globally as a method to automate species population estimates from camera trap images.

Year of Publication
2020
Conference Name
Proceedings - 2020 IEEE Winter Conference on Applications of Computer Vision Workshops, WACVW 2020
ISBN Number
9781728171623
DOI
10.1109/WACVW50321.2020.9096925