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Full-Text Articles in Engineering
Accelerating Machine Learning Inference For Satellite Component Feature Extraction Using Fpgas., Andrew Ekblad
Accelerating Machine Learning Inference For Satellite Component Feature Extraction Using Fpgas., Andrew Ekblad
Theses and Dissertations
Running computer vision algorithms requires complex devices with lots of computing power, these types of devices are not well suited for space deployment. The harsh radiation environment and limited power budgets have hindered the ability of running advanced computer vision algorithms in space. This problem makes running an on-orbit servicing detection algorithm very difficult. This work proposes using a low powered FPGA to accelerate the computer vision algorithms that enable satellite component feature extraction. This work uses AMD/Xilinx’s Zynq SoC and DPU IP to run model inference. Experiments in this work centered around improving model post processing by creating implementations …
Wireless Environmental Weather Monitor, Joel Christie-Millett, Nathan Schroeder, Sylvester Wilson, Matthew Szijarto
Wireless Environmental Weather Monitor, Joel Christie-Millett, Nathan Schroeder, Sylvester Wilson, Matthew Szijarto
Williams Honors College, Honors Research Projects
The goal of this senior design/honors project is to create a device that monitors environmental conditions in order to detect a wildfire. This device should notify a user of the status of the environment. The device should also last for 6 months without any human interaction. My role on the team is to design the power supply system that maximizes efficiency and uses renewable energy.