3 citations · 5 across the 5 of their papers we have counts for
6 papers · 1 filter
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…
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…
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…
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…
Presence-Only Geographical Priors for Fine-Grained Image Classification
Oisin Mac Aodha, Elijah Cole, Pietro Perona
Appearance information alone is often not sufficient to accurately differentiate between fine-grained visual categories. Human experts make use of additional cues such as where, an…