Imperial College London

Professor Peter Y. K. Cheung

Faculty of EngineeringDyson School of Design Engineering

Head of the Dyson School of Design Engineering
 
 
 
//

Contact

 

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

 
 
//

Assistant

 

Mrs Wiesia Hsissen +44 (0)20 7594 6261

 
//

Location

 

910BElectrical EngineeringSouth Kensington Campus

//

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}
}

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 -