Artikel mit Open-Access-Mandaten - Lita YangWeitere Informationen
Nicht verfügbar: 5
SRAM voltage scaling for energy-efficient convolutional neural networks
L Yang, B Murmann
2017 18th International Symposium on Quality Electronic Design (ISQED), 7-12, 2017
Mandate: US Department of Defense
Bit error tolerance of a CIFAR-10 binarized convolutional neural network processor
L Yang, D Bankman, B Moons, M Verhelst, B Murmann
2018 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5, 2018
Mandate: US Department of Defense
Approximate SRAM for energy-efficient, privacy-preserving convolutional neural networks
L Yang, B Murmann
2017 IEEE Computer Society Annual Symposium on VLSI (ISVLSI), 689-694, 2017
Mandate: US Department of Defense
TRIG: Hardware accelerator for inference-based applications and experimental demonstration using carbon nanotube FETs
G Hills, D Bankman, B Moons, L Yang, J Hillard, A Kahng, R Park, ...
Proceedings of the 55th Annual Design Automation Conference, 1-10, 2018
Mandate: US National Science Foundation, US Department of Defense
Cognitive computation and communication: A complement solution to cloud for IoT
N Nguyen-Thanh, L Yang, DHN Nguyen, C Jabbour, B Murmann
2016 International Conference on Advanced Technologies for Communications …, 2016
Mandate: European Commission
Verfügbar: 2
An Always-On 3.8 J/86% CIFAR-10 Mixed-Signal Binary CNN Processor With All Memory on Chip in 28-nm CMOS
D Bankman, L Yang, B Moons, M Verhelst, B Murmann
IEEE Journal of Solid-State Circuits 54 (1), 158-172, 2018
Mandate: US Department of Defense, European Commission
Three-dimensional stacked neural network accelerator architectures for AR/VR applications
L Yang, RM Radway, YH Chen, TF Wu, H Liu, E Ansari, V Chandra, ...
IEEE Micro 42 (6), 116-124, 2022
Mandate: US Department of Defense
Angaben zur Publikation und Finanzierung werden automatisch von einem Computerprogramm ermittelt