114 citations · 193 across the 19 of their papers we have counts for
5 papers · 1 filter
Consensus-Driven Active Model Selection
Justin Kay, Grant Van Horn, Subhransu Maji +2
The widespread availability of off-the-shelf machine learning models poses a challenge: which model, of the many available candidates, should be chosen for a given data analysis ta…
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…
WILDS: A Benchmark of in-the-Wild Distribution Shifts
Pang Wei Koh, Shiori Sagawa, Henrik Marklund +20
Distribution shifts -- where the training distribution differs from the test distribution -- can substantially degrade the accuracy of machine learning (ML) systems deployed in the…
A deep active learning system for species identification and counting in camera trap images
Mohammad Sadegh Norouzzadeh, Dan Morris, Sara Beery +3
Biodiversity conservation depends on accurate, up-to-date information about wildlife population distributions. Motion-activated cameras, also known as camera traps, are a critical…