Application of Machine Learning Tools for Waterbird Colony Monitoring Provides Gains in Precision and Temporal Efficiency
Anna Vallery, Krish Kabra, Richard Gibbons, Hank Arnold, Nicholas Minnich, Arko Barman
The paper compares four waterbird monitoring methods using drone imagery, finding that fully automated detection reduces annotation time by 98% while maintaining 87% accuracy.
bioRxiv · Jul 2, 2026 · PreprintEcology