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Trevor C. Vannoy
at Montana State Univ
SPIE Involvement:
Author
Area of Expertise:
Signal processing , Machine learning , FPGAs
Profile Summary
Trevor C. Vannoy received his BS and MS in electrical engineering from Montana State University, where he is currently pursuing a PhD in electrical engineering. His research interests include signal processing, machine learning, field-programmable gate arrays, and real-time algorithms for embedded systems.
Publications (4)
Proceedings Article | 4 October 2023 Presentation + Paper
Preliminary analysis of drone propeller signals using wingbeat-modulation lidar
John Fike, Trevor Vannoy, Nathaniel Sweeney, Joseph Shaw, Bradley Whitaker
Proceedings Volume 12675, 126750R (2023) https://doi.org/10.1117/12.2676175
KEYWORDS: LIDAR, Unmanned aerial vehicles, Machine learning, Pulse signals, Data modeling, Photomultipliers, Neural networks, Feature extraction, Active remote sensing, Digital signal processing
Proceedings Article | 3 June 2022 Presentation + Paper
Automated insect recognition in unlabeled lidar field measurements
Hannah Madsen, Trevor Vannoy, Elizabeth Rehbein, Riley Logan, Joseph Shaw, Bradley Whitaker
Proceedings Volume 12110, 1211007 (2022) https://doi.org/10.1117/12.2618660
KEYWORDS: Data modeling, LIDAR, Neural networks, Machine learning, Evolutionary algorithms, Target detection, Remote sensing, Polarization, Modulation, Matrices
Proceedings Article | 27 May 2022 Presentation + Paper
Toward a hardware implementation of lidar-based real-time insect detection
Proceedings Volume 12102, 121020E (2022) https://doi.org/10.1117/12.2618970
KEYWORDS: MATLAB, Field programmable gate arrays, Simulink, LIDAR, Feature extraction, Neural networks, Digital signal processing, Machine learning, Algorithm development
SPIE Journal Paper | 19 July 2021
Machine learning-based region of interest detection in airborne lidar fisheries surveys
JARS, Vol. 15, Issue 03, 038503, (July 2021) https://doi.org/10.1117/12.10.1117/1.JRS.15.038503
KEYWORDS: LIDAR, Neural networks, Machine learning, Inspection, Polarization, MATLAB, Optical inspection, Visualization, Telescopes, Evolutionary algorithms
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