Date of Submission

Fall 2018

Academic Programs and Concentrations

Computer Science

Project Advisor 1

Sven Anderson

Abstract/Artist's Statement

Xenopus laevis tadpoles are a useful animal model for neurobiology research because they provide a means to study the development of the brain in a species that is both physiologically well-understood and logistically easy to maintain in the laboratory. For behavioral studies, however, their individual and social swimming patterns represent a largely untapped trove of data, due to the lack of a computational tool that can accurately track multiple tadpoles at once in video feeds. This paper presents a system that was developed to accomplish this task, which can reliably track up to six tadpoles in a controlled environment, thereby enabling new research studies that were previously not feasible.

Open Access Agreement

Open Access

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Alexander_Hamme_Senior_Project_Code.tar.gz (183311 kB)
The entire set of code created in the development of this project, along with the trained neural network model file.

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