%0 Conference Paper %1 conf/asscc/LeeSY17 %A Lee, Jinmook %A Shin, Dongjoo %A Yoo, Hoi-Jun %B A-SSCC %D 2017 %I IEEE %K dblp %P 237-240 %T A 21mW low-power recurrent neural network accelerator with quantization tables for embedded deep learning applications. %U http://dblp.uni-trier.de/db/conf/asscc/asscc2017.html#LeeSY17 %@ 978-1-5386-3178-2

@inproceedings{conf/asscc/LeeSY17, added-at = {2018-01-05T00:00:00.000+0100}, author = {Lee, Jinmook and Shin, Dongjoo and Yoo, Hoi-Jun}, biburl = {https://www.bibsonomy.org/bibtex/2c733467bc5ec760006a42193475ea920/dblp}, booktitle = {A-SSCC}, crossref = {conf/asscc/2017}, ee = {https://doi.org/10.1109/ASSCC.2017.8240260}, interhash = {d71a85681999c2aa1751dcc90154e4da}, intrahash = {c733467bc5ec760006a42193475ea920}, isbn = {978-1-5386-3178-2}, keywords = {dblp}, pages = {237-240}, publisher = {IEEE}, timestamp = {2018-01-06T11:34:28.000+0100}, title = {A 21mW low-power recurrent neural network accelerator with quantization tables for embedded deep learning applications.}, url = {http://dblp.uni-trier.de/db/conf/asscc/asscc2017.html#LeeSY17}, year = 2017 }