Header

UZH-Logo

Maintenance Infos

High-Accuracy and Energy-Efficient Acoustic Inference using Hardware-Aware Training and a 0.34nW/Ch Full-Wave Rectifier


Zhou, Sheng; Chen, Xi; Kim, Kwantae; Liu, Shih-Chii (2023). High-Accuracy and Energy-Efficient Acoustic Inference using Hardware-Aware Training and a 0.34nW/Ch Full-Wave Rectifier. In: 2023 IEEE 5th International Conference on Artificial Intelligence Circuits and Systems (AICAS), Hangzhou, China, 11 June 2023 - 13 June 2023, Institute of Electrical and Electronics Engineers.

Statistics

Citations

Dimensions.ai Metrics

Altmetrics

Downloads

20 downloads since deposited on 21 Nov 2023
20 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Neuroinformatics
Dewey Decimal Classification:570 Life sciences; biology
Scopus Subject Areas:Physical Sciences > Artificial Intelligence
Physical Sciences > Computer Vision and Pattern Recognition
Physical Sciences > Hardware and Architecture
Physical Sciences > Information Systems
Physical Sciences > Electrical and Electronic Engineering
Language:English
Event End Date:13 June 2023
Deposited On:21 Nov 2023 12:48
Last Modified:22 Nov 2023 21:00
Publisher:Institute of Electrical and Electronics Engineers
Series Name:IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS)
ISBN:9798350332674
OA Status:Green
Publisher DOI:https://doi.org/10.1109/aicas57966.2023.10168561
Project Information:
  • : FunderNational Science Foundation
  • : Grant ID
  • : Project Title
  • Content: Accepted Version
  • Language: English