LEADER 01704nam  2200433z- 450 
001 9910476900503321
005 20210528
010   $a1000104538
035   $a(CKB)5470000000567018
035   $a(oapen)https://directory.doabooks.org/handle/20.500.12854/70074
035   $a(oapen)doab70074
035   $a(EXLCZ)995470000000567018
100   $a20202105d2021      |y         0
101 0 $aeng
135   $aurmn|---annan
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 00$aRoad Condition Estimation with Data Mining Methods using Vehicle Based Sensors
210   $aKarlsruhe$cKIT Scientific Publishing$d2021
215   $a1 online resource (234 p.)
225 1 $aKarlsruher Schriftenreihe Fahrzeugsystemtechnik
311 08$a3-7315-1004-9 
330   $aThe 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.
606   $aMechanical engineering & materials$2bicssc
610   $aFahrzeugsensorik
610   $aFahrzeugtechnik
610   $aMaschine Learning
610   $aMaschinelles Lernen
610   $aRoad Condition
610   $aStraßenscha?den
610   $aVehicle Sensors
610   $aVehicle Technology
615  7$aMechanical engineering & materials
700   $aMasino$b Johannes$4auth$01319299
906   $aBOOK
912   $a9910476900503321
996   $aRoad Condition Estimation with Data Mining Methods using Vehicle Based Sensors$93033730
997   $aUNINA