Christopher McEnaney
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Researcher
Graduate Student Researcher
Research Areas
Biography and Research Information
OverviewAI-generated summary
Christopher McEnaney's research focuses on developing computational frameworks for behavioral analysis, particularly in the field of ethology. His recent work has involved the creation of a machine learning framework designed to automate the process of computational ethology through markerless pose estimation. This approach aims to enhance the efficiency and accuracy of analyzing animal behavior from video data.
McEnaney has collaborated with several researchers at the University of Arkansas at Fayetteville, including Xintao Wu, Amy R. Poe, Minh-Hao Van, and Prateek Verma, contributing to one shared publication with each. His current academic standing is as a graduate student at the University of Arkansas.
Metrics
- Publications: 1
Selected Publications
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A Machine Learning Framework for Automated Computational Ethology Using Markerless Pose Estimation (2025)
Collaboration Network
Top Collaborators
- A Machine Learning Framework for Automated Computational Ethology Using Markerless Pose Estimation
- A Machine Learning Framework for Automated Computational Ethology Using Markerless Pose Estimation
- A Machine Learning Framework for Automated Computational Ethology Using Markerless Pose Estimation
- A Machine Learning Framework for Automated Computational Ethology Using Markerless Pose Estimation
- A Machine Learning Framework for Automated Computational Ethology Using Markerless Pose Estimation
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