733 citations · 1.3k across the 29 of their papers we have counts for
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Extending the WILDS Benchmark for Unsupervised Adaptation
Shiori Sagawa, Pang Wei Koh, Tony Lee +17
Machine learning systems deployed in the wild are often trained on a source distribution but deployed on a different target distribution. Unlabeled data can be a powerful point of…
Seeing biodiversity: perspectives in machine learning for wildlife conservation
Devis Tuia, Benjamin Kellenberger, Sara Beery +15
Data acquisition in animal ecology is rapidly accelerating due to inexpensive and accessible sensors such as smartphones, drones, satellites, audio recorders and bio-logging device…
Domain Adaptation for Rare Classes Augmented with Synthetic Samples
Tuhin Das, Robert-Jan Bruintjes, Attila Lengyel +2
To alleviate lower classification performance on rare classes in imbalanced datasets, a possible solution is to augment the underrepresented classes with synthetic samples. Domain…
Species Distribution Modeling for Machine Learning Practitioners: A Review
Sara Beery, Elijah Cole, Joseph Parker +2
Conservation science depends on an accurate understanding of what's happening in a given ecosystem. How many species live there? What is the makeup of the population? How is that c…
ElephantBook: A Semi-Automated Human-in-the-Loop System for Elephant Re-Identification
Peter Kulits, Jake Wall, Anka Bedetti +2
African elephants are vital to their ecosystems, but their populations are threatened by a rise in human-elephant conflict and poaching. Monitoring population dynamics is essential…
Image-to-Image Translation of Synthetic Samples for Rare Classes
Edoardo Lanzini, Sara Beery
The natural world is long-tailed: rare classes are observed orders of magnitudes less frequently than common ones, leading to highly-imbalanced data where rare classes can have onl…
Can poachers find animals from public camera trap images?
Sara Beery, Elizabeth Bondi
To protect the location of camera trap data containing sensitive, high-target species, many ecologists randomly obfuscate the latitude and longitude of the camera when publishing t…
The iWildCam 2021 Competition Dataset
Sara Beery, Arushi Agarwal, Elijah Cole +1
Camera traps enable the automatic collection of large quantities of image data. Ecologists use camera traps to monitor animal populations all over the world. In order to estimate t…
Benchmarking Representation Learning for Natural World Image Collections
Grant Van Horn, Elijah Cole, Sara Beery +3
Recent progress in self-supervised learning has resulted in models that are capable of extracting rich representations from image collections without requiring any explicit label s…