Roadmap on signal processing for next generation measurement systems

Simple item page
dc.citation.issue1
dc.citation.volume33
dc.contributor.authorIakovidis DK
dc.contributor.authorOoi M
dc.contributor.authorKuang YC
dc.contributor.authorDemidenko S
dc.contributor.authorShestakov A
dc.contributor.authorSinitsin V
dc.contributor.authorHenry M
dc.contributor.authorSciacchitano A
dc.contributor.authorDiscetti S
dc.contributor.authorDonati S
dc.contributor.authorNorgia M
dc.contributor.authorMenychtas A
dc.contributor.authorMaglogiannis I
dc.contributor.authorWriessnegger SC
dc.contributor.authorChacon LAB
dc.contributor.authorDimas G
dc.contributor.authorFilos D
dc.contributor.authorAletras AH
dc.contributor.authorTöger J
dc.contributor.authorDong F
dc.contributor.authorRen S
dc.contributor.authorUhl A
dc.contributor.authorPaziewski J
dc.contributor.authorGeng J
dc.contributor.authorFioranelli F
dc.contributor.authorNarayanan RM
dc.contributor.authorFernandez C
dc.contributor.authorStiller C
dc.contributor.authorMalamousi K
dc.contributor.authorKamnis S
dc.contributor.authorDelibasis K
dc.contributor.authorWang D
dc.contributor.authorZhang J
dc.contributor.authorGao RX
dc.date.accessioned2023-10-15T23:51:13Z
dc.date.accessioned2023-10-19T20:38:32Z
dc.date.available2021-11-16
dc.date.available2023-10-15T23:51:13Z
dc.date.available2023-10-19T20:38:32Z
dc.date.issued2022-01-01
dc.date.updated2023-10-15T23:29:33Z
dc.description.abstractSignal processing is a fundamental component of almost any sensor-enabled system, with a wide range of applications across different scientific disciplines. Time series data, images, and video sequences comprise representative forms of signals that can be enhanced and analysed for information extraction and quantification. The recent advances in artificial intelligence and machine learning are shifting the research attention towards intelligent, data-driven, signal processing. This roadmap presents a critical overview of the state-of-the-art methods and applications aiming to highlight future challenges and research opportunities towards next generation measurement systems. It covers a broad spectrum of topics ranging from basic to industrial research, organized in concise thematic sections that reflect the trends and the impacts of current and future developments per research field. Furthermore, it offers guidance to researchers and funding agencies in identifying new prospects.
dc.description.confidentialfalse
dc.edition.editionJanuary 2022
dc.identifierARTN 012002
dc.identifierhttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000719572900001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=c5bb3b2499afac691c2e3c1a83ef6fef
dc.identifier.citationIakovidis DK, Ooi M, Kuang YC, Demidenko S, Shestakov A, Sinitsin V, Henry M, Sciacchitano A, Discetti S, Donati S, Norgia M, Menychtas A, Maglogiannis I, Wriessnegger SC, Chacon LAB, Dimas G, Filos D, Aletras AH, Töger J, Dong F, Ren S, Uhl A, Paziewski J, Geng J, Fioranelli F, Narayanan RM, Fernandez C, Stiller C, Malamousi K, Kamnis S, Delibasis K, Wang D, Zhang J, Gao RX. (2022). Roadmap on signal processing for next generation measurement systems. Measurement Science and Technology. 33. 1.
dc.identifier.doi10.1088/1361-6501/ac2dbd
dc.identifier.eissn1361-6501
dc.identifier.elements-typejournal-article
dc.identifier.harvestedMassey_Dark
dc.identifier.issn0957-0233
dc.identifier.urihttp://hdl.handle.net/10179/20327
dc.languageEnglish
dc.publisherIOP Publishing
dc.publisher.urihttps://iopscience.iop.org/article/10.1088/1361-6501/ac2dbd
dc.relation.isPartOfMeasurement Science and Technology
dc.rights(c) The Author/sen_US
dc.rightsCC BY 4.0en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.subjectsignal processing
dc.subjectmeasurement systems
dc.subjectoptical measurements
dc.subjectmachine learning
dc.subjectbiomedical applications
dc.subjectenvironmental applications
dc.subjectindustrial applications
dc.titleRoadmap on signal processing for next generation measurement systems
dc.typeJournal article
pubs.elements-id450104
pubs.organisational-groupOther
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
450104 PDF.pdf
Size:
6.64 MB
Format:
Adobe Portable Document Format
Description:
Download
Collections
Journal Articles