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Smart city article details

Title	A Cnn-Based Vehicle Identification Solution In Parking System With Hardware Accelerator On Fpga
ID_Doc	685
Authors	Nghi H.P.; Thinh T.N.
Year	2022
Published	Proceedings - 2022 RIVF International Conference on Computing and Communication Technologies, RIVF 2022
DOI	http://dx.doi.org/10.1109/RIVF55975.2022.10013847
Abstract	The process of searching for parking lots of current drivers is mainly based on travel experience and static instructions on the street, which consumes a lot of time, costs, affects traffic safety and urban growth rate of the city. Therefore, the application of technology in parking assistance is one of the urgent issues, one of the basic factors contributing to the creation of a smart city model. In this paper, we have implemented a smart parking license plate recognition application applying Deep Learning technology using convolutional neural network (CNN) on programmable hardware Xilinx Zynq UltraScale+ MPSoC, a low-latency, low-energy with good accuracy device. The experimental result of our CNN accelerator design has real-time response with mAP drop less than 4%, the throughput is increased by approximately 1.25 times, and the energy consumption is reduced by 2.56 times than the same model on Jetson Nano. © 2022 IEEE.
Author Keywords	CNN; embedded systems; FPGA; hardware accelerator; smart parking

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