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dc.contributor.authorMasino, Johannes
dc.date.accessioned2021-05-27T09:28:12Z
dc.date.available2021-05-27T09:28:12Z
dc.date.issued2021
dc.identifierONIX_20210527_9783731510048_19
dc.identifier.issn1869-6058
dc.identifier.urihttps://library.oapen.org/handle/20.500.12657/48822
dc.description.abstractThe work provides novel methods to process inertial sensor and acoustic sensor data for road condition estimation and monitoring with application in vehicles, which serve as sensor platforms. Furthermore, methods are introduced to combine the results from various vehicles for a more reliable estimation.
dc.languageEnglish
dc.relation.ispartofseriesKarlsruher Schriftenreihe Fahrzeugsystemtechnik
dc.subject.classificationbic Book Industry Communication::T Technology, engineering, agriculture::TG Mechanical engineering & materials
dc.subject.classificationthema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materialsen_US
dc.subject.otherMaschinelles Lernen
dc.subject.otherFahrzeugtechnik
dc.subject.otherStraßenschäden
dc.subject.otherFahrzeugsensorik
dc.subject.otherMaschine Learning
dc.subject.otherVehicle Technology
dc.subject.otherRoad Condition
dc.subject.otherVehicle Sensors
dc.titleRoad Condition Estimation with Data Mining Methods using Vehicle Based Sensors
dc.typebook
oapen.identifier.doi10.5445/KSP/1000104538
oapen.relation.isPublishedBy44e29711-8d53-496b-85cc-3d10c9469be9
oapen.relation.isbn9783731510048
oapen.series.number77
oapen.pages234
oapen.place.publicationKarlsruhe
peerreview.anonymityAll identities known
peerreview.id51a542ec-eaeb-47c2-861d-6022e981a97a
peerreview.open.reviewNo
peerreview.publish.responsibilityBooks or series editor
peerreview.review.stagePre-publication
peerreview.review.typeFull text
peerreview.reviewer.typeEditorial board member
peerreview.reviewer.typeExternal peer reviewer
peerreview.titleDissertations in Series (Dissertationen in Schriftenreihe)


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