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What is FPGA-Based Machine Learning for UAV Edge Detection about?

This article presents a machine learning algorithm implemented on a field programmable gate array (FPGA) for image edge detection in unmanned aerial vehicles (UAVs). The proposed support vector regression (SVR) model, enhanced by dynamic partial reconfiguration (DPR), significantly reduces computational load and processing time, achieving a speed 68 times faster than software implementations with low power consumption. The system demonstrates a high success rate of 99.18% in pose estimation, making it suita

Author

nithya.varsha1

Language

EN