Breathing-based authentication on resource-constrained IoT devices using recurrent neural networks
Recurrent neural networks (RNNs) have shown promising resultsin audio and speech-processing applications. The increasingpopularity of Internet of Things (IoT) devices makes a strongcase for implementing RNN-based inferences for applicationssuch as acoustics-based authentication and voice commandsfor...
Saved in:
Main Authors: | CHAUHAN, Jagmohan, SENEVIRATNE, Suranga, HU, Yining, MISRA, Archan, SENEVIRATNE, Aruna, LEE, Youngki |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2018
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/4054 https://ink.library.smu.edu.sg/context/sis_research/article/5057/viewcontent/08364655__1_.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
Performance characterization of deep learning models for breathing-based authentication on resource-constrained devices
by: CHAUHAN, Jagmohan, et al.
Published: (2018) -
BreathPrint: Breathing acoustics-based user authentication
by: CHAUHAN, Jagmohan, et al.
Published: (2017) -
Decision theory for network security: Active sensing for detection and prevention of data exfiltration
by: MC CARTHY, Sara, et al.
Published: (2020) -
Interaction-aware arrangement for event-based social networks
by: KOU, Feifei, et al.
Published: (2019) -
A quantitative analysis framework for recurrent neural network
by: DU, Xiaoning, et al.
Published: (2019)