Output list
Conference poster
Building Pinball Machines in a STEM Fabrication Course
Date presented 08/06/2025
International Symposium on Academic Makerspaces, 08/06/2025–08/07/2025, Berkeley, CA
Pinball machines combine art and engineering in a fun project for teaching a broad range of maker skills Eckerd offers a two-semester STEM course designed to increase the number of students majoring in physics, math, and computer science. The first semester teaches digital fabrication, CAD, microcontroller-based electronics and programming. Students put these skills to use in the second semester by designing and building full-sized pinball machines.
Conference poster
Using machine learning to identify gopher tortoise individuals
Date presented 11/12/2022
2022 Gopher Tortoise Council Annual Meeting, 11/11/2022–11/13/2022, Freeport, Florida
Camera traps are increasingly being used as a research tool in behavioral ecology to observe animals in the field. One challenge of continuous data collection by camera traps is that the amount of data produced can be overwhelming to process manually. Machine learning techniques show promise for becoming important tools to meet this challenge in a time- and cost-effective way. Over the past year, we collected images of over 950 social interactions among gopher tortoises from twelve active tortoise burrows at Boyd Hill Nature Preserve in St. Petersburg, Florida. The individual tortoises in each interaction must be identified to comprehensively analyze this data. To automate the re-identification step, we developed a machine learning algorithm to distinguish between tortoises. It takes a large amount of data to train the machine learning algorithm to recognize patterns. Therefore, we describe how our training dataset was collected and created. We also recount how we trained a Siamese neural network to identify individual tortoises based on their carapace markings in a manner similar to how facial recognition is used on humans. This research demonstrates that machine learning has the potential to be a powerful tool to aid data processing and analysis in behavioral ecology.
Conference poster
An Image Processing Pipeline for Camera Trap Time-Lapse Recordings
Date presented 06/20/2022
Computer Vision For Animals, 06/20/2022–06/20/2022, New Orleans
A new open-source image processing pipeline for analyzing camera trap time-lapse recordings is described. This pipeline includes machine learning models to assist human-in-the-loop video segmentation and animal re-identification. We present some performance results and observations on the utility of this pipeline after using it in a year-long project studying the spatial ecology and social behavior of the gopher tortoise.