Hardware Acceleration for Object Detection using YOLOv5 Deep Learning Algorithm on Xilinx Zynq FPGA Platform

Hardware Acceleration for Object Detection using YOLOv5 Deep Learning Algorithm on Xilinx Zynq FPGA Platform

Object recognition presents considerable difficulties within the domain of computer vision. Field-Programmable Gate Arrays (FPGAs) offer a flexible hardware platform, having exceptional computing capabilities due to their adaptable topologies, enabling highly parallel, high-performance, and diverse...

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Bibliographic Details
Main Authors: Taoufik Saidani, Refka Ghodhbani, Ahmed Alhomoud, Ahmad Alshammari, Hafedh Zayani, Mohammed Ben Ammar
Format: Article
Language:English
Published: D. G. Pylarinos 2024-02-01
Series:Engineering, Technology & Applied Science Research
Subjects:
object detection
YOLOv5
high level synthesis
FPGA
HDL coder
Online Access:https://etasr.com/index.php/ETASR/article/view/6761

Internet

https://etasr.com/index.php/ETASR/article/view/6761

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