FPGA-Based Acceleration of Convolutional Neural Network for Gesture Recognition Using mm-Wave FMCW Radar-Reference-Cited by-同舟云学术

FPGA-Based Acceleration of Convolutional Neural Network for Gesture Recognition Using mm-Wave FMCW Radar

Published:2022-10-25 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE Nordic Circuits and Systems Conference (NorCAS)
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Author:

Syed Rizwan Tariq¹,Zhao Yanhua¹,Ulbricht Markus¹,Sark Vladica¹,Krstic Milos¹

Affiliation:

1. IHP - Leibniz-Institut für innovative Mikroelektronik,Frankfurt (Oder),Germany

Funder

Federal Ministry of Education and Research of Germany

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9933920/9934110/09934412.pdf?arnumber=9934412

Reference35 articles.

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4. Reliability Evaluation of Pruned Neural Networks against Errors on Parameters;gao;2020 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT) IEEE,0

5. Vitis High-Level Synthesis User Guide (UG1399);Xilinx,2022

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1. A Hardware and Software Co-Design for Energy-Efficient Neural Network Accelerator With Multiplication-Less Folded-Accumulative PE for Radar-Based Hand Gesture Recognition;IEEE Transactions on Very Large Scale Integration (VLSI) Systems;2024

2. Data Set Development for Gesture Recognition and Implementation using MATLAB and Xilinx Vivado;2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques (EASCT);2023-10-20