activity
20192021
most citedThe iWildCam 2020 Competition Dataset

3 citations · 5 across the 4 of their papers we have counts for

collaborators

7 papers

cs.LG2021

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…

cs.CV2021

Multi-Label Learning from Single Positive Labels

Elijah Cole, Oisin Mac Aodha, Titouan Lorieul +3

Predicting all applicable labels for a given image is known as multi-label classification. Compared to the standard multi-class case (where each image has only one label), it is co…

cs.CV2021

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…

cs.CV2021

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…

cs.CV20203 cited

The iWildCam 2020 Competition Dataset

Sara Beery, Elijah Cole, Arvi Gjoka

Camera traps enable the automatic collection of large quantities of image data. Biologists all over the world use camera traps to monitor animal populations. We have recently been…

cs.CV20202 cited

The GeoLifeCLEF 2020 Dataset

Elijah Cole, Benjamin Deneu, Titouan Lorieul +6

Understanding the geographic distribution of species is a key concern in conservation. By pairing species occurrences with environmental features, researchers can model the relatio…