@misc{1b9be9a6861447dfae0f90a8992c0df4,
title = "An AI-Based 3D Bat Movement Tracking System at Wind Energy Facilities Using Multi-Thermal Video Cameras",
abstract = "The poster at the 15th Wind Wildlife Research Meeting discusses how to leverage the potential of real-time thermal-imaging methodologies in quantifying nocturnal bat activities at wind turbines, using 3D computer vision techniques within a deep learning framework. This innovation enables the automatic detection and classification of bats, birds, and insects in thermal-imaging videos captured at wind turbine sites, facilitating efficient and accurate data analysis for enhanced understanding and mitigation of bat-wind turbine interactions.",
keywords = "AI, machine learning, object detection, object tracking, stereo vision, wind-wildlife interactions",
author = "Sora Ryu and John Yarbrough and Cris Hein and Samantha Rooney and Jeffery Clerc and Eliot Quon and Michael Sinner and Pietro Bortolotti and Jessica Schipper and Paul Cryan and Bethany Straw",
year = "2024",
language = "American English",
series = "Presented at the 15th Wind Wildlife Research Meeting, 12-15 November 2024, Corpus Christi, Texas",
publisher = "National Renewable Energy Laboratory (NREL)",
address = "United States",
type = "Other",
}