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Estimating Animal Pose Using Deep Learning A Trained Deep Learning Model Outperforms Morphological Analysis, Sanghoon Lee, Jarod Banzon, Kevin Le, Dal Hyung Kim
Estimating Animal Pose Using Deep Learning A Trained Deep Learning Model Outperforms Morphological Analysis, Sanghoon Lee, Jarod Banzon, Kevin Le, Dal Hyung Kim
Computer Sciences and Electrical Engineering Faculty Research
INTRODUCTION: Analyzing animal behavior helps researchers understand their decision-making process and helper tools are rapidly becoming an indispensable part of many interdisciplinary studies. However, researchers are often challenged to estimate animal pose because of the limitation of the tools and its vulnerability to a specific environment. Over the years, deep learning has been introduced as an alternative solution to overcome these challenges.
OBJECTIVES: This study investigates how deep learning models can be applied for the accurate prediction of animal behavior, comparing with traditional morphological analysis based on image pixels.
METHODS: Transparent Omnidirectional Locomotion Compensator (TOLC), a tracking device, is used …