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AuthorThiam, Patrickdc.contributor.author
AuthorBellmann, Peterdc.contributor.author
AuthorKestler, Hans A.dc.contributor.author
AuthorSchwenker, Friedhelmdc.contributor.author
Date of accession2019-12-11T13:43:12Zdc.date.accessioned
Available in OPARU since2019-12-11T13:43:12Zdc.date.available
Date of first publication2019dc.date.issued
Languageendc.language.iso
PublisherUniversität Ulmdc.publisher
Keywordconvolutional neural networksdc.subject
Keywordsignal processingdc.subject
Keywordinformation fusiondc.subject
Keywordpain intensity classificationdc.subject
KeywordNEURAL-NETWORKSdc.subject
Dewey Decimal GroupDDC 540 / Chemistry & allied sciencesdc.subject.ddc
Dewey Decimal GroupDDC 610 / Medicine & healthdc.subject.ddc
TitleExploring Deep Physiological Models for Nociceptive Pain Recognitiondc.title
Resource typeWissenschaftlicher Artikeldc.type
FacultyFakultät für Ingenieurwissenschaften, Informatik und Psychologieuulm.affiliationGeneral
FacultyMedizinische Fakultätuulm.affiliationGeneral
InstitutionInstitut für Medizinische Systembiologieuulm.affiliationSpecific
InstitutionInstitut für Neuroinformatikuulm.affiliationSpecific
DCMI TypeTextuulm.typeDCMI
CategoryPublikationsnachweiseuulm.category
DOI (external)10.3390/s19204503dc.identifier.doiExternal
Source - Title of sourceSensorssource.title
Source - Place of publicationMDPIsource.publisher
Source - Volume19source.volume
Source - Issue20source.issue
Source - Year2019source.year
Source - Article number4503source.articleNumber
Source - eISSN1424-8220source.identifier.eissn
Open AccessDOAJ Golduulm.OA
Suitable communityMedizinische Fakultätuulm.community
Suitable communityFakultät für Ingenieurwissenschaften, Informatik und Psychologieuulm.community
WoS000497864700151uulm.identifier.wos
University Bibliographyjauulm.unibibliographie


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