Imperial College London
Alternate

Professor Peter Y. K. Cheung

Faculty of Engineering, Dyson School of Design Engineering

Professor of Digital Systems
 
 
 
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Contact

 

+44 (0)20 7594 6200p.cheung Website

 
 
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Assistant

 

Mrs Wiesia Hsissen +44 (0)20 7594 6261

 
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Location

 

910BElectrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Wang:2018:10.1109/FCCM.2018.00057,
author = {Wang, E and Davis, JJ and Cheung, P},
doi = {10.1109/FCCM.2018.00057},
pages = {223--223},
publisher = {IEEE},
title = {A PYNQ-based Framework for Rapid CNN Prototyping},
url = {http://dx.doi.org/10.1109/FCCM.2018.00057},
year = {2018}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - This work presents a self-contained and modifiable framework for fast and easy convolutional neural network prototyping on the Xilinx PYNQ platform. With a Python-based programming interface, the framework combines the convenience of high-level abstraction with the speed of optimised FPGA implementation. Our work is freely available on GitHub for the community to use and build upon.
AU  - Wang,E
AU  - Davis,JJ
AU  - Cheung,P
DO  - 10.1109/FCCM.2018.00057
EP  - 223
PB  - IEEE
PY  - 2018///
SP  - 223
TI  - A PYNQ-based Framework for Rapid CNN Prototyping
UR  - http://dx.doi.org/10.1109/FCCM.2018.00057
UR  - https://ieeexplore.ieee.org/document/8457672/
UR  - http://hdl.handle.net/10044/1/57937
ER  -
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