Energy-efficient neural network chips approach human recognition capabilities

Research output: Contribution to journal › Article › peer-review

Original language	English
Pages (from-to)	11387-11389
Number of pages	3
Journal	Proceedings of the National Academy of Sciences of the United States of America
Volume	113
Issue number	41
DOIs	https://doi.org/10.1073/pnas.1614109113
Publication status	Published - 2016

Fields of Expertise

@article{0b2421ee3f9f4310a770eb142ffe0a98,

title = "Energy-efficient neural network chips approach human recognition capabilities",

author = "Wolfgang Maass",

year = "2016",

doi = "10.1073/pnas.1614109113",

language = "English",

volume = "113",

pages = "11387--11389",

journal = "Proceedings of the National Academy of Sciences of the United States of America",

issn = "0027-8424",

publisher = "National Academy of Sciences ",

number = "41",

}

TY - JOUR

T1 - Energy-efficient neural network chips approach human recognition capabilities

AU - Maass, Wolfgang

PY - 2016

Y1 - 2016

U2 - 10.1073/pnas.1614109113

DO - 10.1073/pnas.1614109113

M3 - Article

VL - 113

SP - 11387

EP - 11389

JO - Proceedings of the National Academy of Sciences of the United States of America

JF - Proceedings of the National Academy of Sciences of the United States of America

SN - 0027-8424

IS - 41

ER -