Enhancing Vehicular Safety in Adverse Weather Using Computer Vision Analysis
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: 2014شناسه الکترونیک: 10.1109/IGBSG.2014.6835279
کلیدواژه(گان): compressed sensing,n estimation theory,n least mean squares methods,n matrix algebra,n radio networks,n stochastic processes,n M2M networks,n MMSE estimator,n estimation error upper bound,n low-complexity remote compressive sensing,n low-complexity sensing matrix,n machine-to-machine networks,n minimum mean square error,n noiseless stochastic CS problem,n power law,n redundant information transmission,n remote CS scheme,n selected power exponent
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Enhancing Vehicular Safety in Adverse Weather Using Computer Vision Analysis
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contributor author | Lin, Che-Tsung | |
contributor author | Lin, Yu-Chen | |
contributor author | Chen, Long-Tai | |
contributor author | Wang, Yuan-Fang | |
date accessioned | 2020-03-12T21:55:40Z | |
date available | 2020-03-12T21:55:40Z | |
date issued | 2014 | |
identifier other | 6965965.pdf | |
identifier uri | http://libsearch.um.ac.ir:80/fum/handle/fum/1065404 | |
format | general | |
language | English | |
publisher | IEEE | |
title | Enhancing Vehicular Safety in Adverse Weather Using Computer Vision Analysis | |
type | Conference Paper | |
contenttype | Metadata Only | |
identifier padid | 8198811 | |
subject keywords | compressed sensing | |
subject keywords | n estimation theory | |
subject keywords | n least mean squares methods | |
subject keywords | n matrix algebra | |
subject keywords | n radio networks | |
subject keywords | n stochastic processes | |
subject keywords | n M2M networks | |
subject keywords | n MMSE estimator | |
subject keywords | n estimation error upper bound | |
subject keywords | n low-complexity remote compressive sensing | |
subject keywords | n low-complexity sensing matrix | |
subject keywords | n machine-to-machine networks | |
subject keywords | n minimum mean square error | |
subject keywords | n noiseless stochastic CS problem | |
subject keywords | n power law | |
subject keywords | n redundant information transmission | |
subject keywords | n remote CS scheme | |
subject keywords | n selected power exponent | |
identifier doi | 10.1109/IGBSG.2014.6835279 | |
journal title | ehicular Technology Conference (VTC Fall), 2014 IEEE 80th | |
filesize | 1384383 | |
citations | 0 |