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Bayesian, maneuver-based, long-term trajectory prediction and criticality assessment for driver assistance systems

contributor authorSchreier, Matthias
contributor authorWillert, Volker
contributor authorAdamy, Jurgen
date accessioned2020-03-12T21:46:10Z
date available2020-03-12T21:46:10Z
date issued2014
identifier other6957713.pdf
identifier urihttps://libsearch.um.ac.ir:443/fum/handle/fum/1059806?locale-attribute=fa&show=full
formatgeneral
languageEnglish
publisherIEEE
titleBayesian, maneuver-based, long-term trajectory prediction and criticality assessment for driver assistance systems
typeConference Paper
contenttypeMetadata Only
identifier padid8191385
subject keywordsdata acquisition
subject keywordsn pattern classification
subject keywordsn radiofrequency identification
subject keywordsn smart phones
subject keywordsn NFC function
subject keywordsn RFID tagging
subject keywordsn RFID-based annotations
subject keywordsn daily life
subject keywordsn expert-verified annotations
subject keywordsn expert-verified variant
subject keywordsn pattern classification
subject keywordsn personalised phone placement recognition
subject keywordsn phone placement recordings
subject keywordsn phone sites
subject keywordsn phone-integrated sensors
subject keywordsn smartphones
subject keywordsn training data acquisition
subject keywordsn Accuracy
subject keywordsn Context
subject keywordsn Context modeling
subject keywordsn Data
identifier doi10.1109/PerComW.2014.6815159
journal titlentelligent Transportation Systems (ITSC), 2014 IEEE 17th International Conference on
filesize769306
citations0


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