•  Home
  • Library
  • DRO home
Submit research Contact DRO

DRO

Data-aided Sensing for Gaussian Process Regression in IoT Systems

Choi, Jinho 2020, Data-aided Sensing for Gaussian Process Regression in IoT Systems, IEEE Internet of Things Journal, vol. 8, no. 9, pp. 7717-7726, doi: 10.1109/JIOT.2020.3040676.

Attached Files
Name Description MIMEType Size Downloads

Title Data-aided Sensing for Gaussian Process Regression in IoT Systems
Author(s) Choi, JinhoORCID iD for Choi, Jinho orcid.org/0000-0002-4895-6680
Journal name IEEE Internet of Things Journal
Volume number 8
Issue number 9
Start page 7717
End page 7726
Total pages 10
Publisher IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Publication date 2020-01-01
ISSN 2327-4662
2327-4662
Keyword(s) Science & Technology
Technology
Computer Science, Information Systems
Engineering, Electrical & Electronic
Telecommunications
Computer Science
Engineering
Active learning
data-aided sensing (DAS)
Gaussian process regression (GPR)
INTERNET
Language eng
DOI 10.1109/JIOT.2020.3040676
Field of Research 0805 Distributed Computing
1005 Communications Technologies
HERDC Research category C1 Refereed article in a scholarly journal
Persistent URL http://hdl.handle.net/10536/DRO/DU:30146408

Document type: Journal Article
Collections: Faculty of Science, Engineering and Built Environment
School of Information Technology
Related Links
Link Description
Connect to published version
Go to link with your DU access privileges
 
Connect to Elements publication management system
Go to link with your DU access privileges
 
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 2 times in TR Web of Science
Scopus Citation Count Cited 0 times in Scopus Google Scholar Search Google Scholar
Access Statistics: 136 Abstract Views, 2 File Downloads  -  Detailed Statistics
Created: Tue, 05 Jan 2021, 13:07:43 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.