A computer vision approach for detection and counting of motorcycle riders in university campus
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سال
: 2014شناسه الکترونیک: 10.1109/CONFLUENCE.2014.6949338
کلیدواژه(گان): cepstral analysis,signal classification,speech recognition,background noise,cepestral coefficient,feature vector,front end analysis,k-NN classification,k-nearest neighbor classification,mel frequency scale,pattern recognition model,pitch period,real-time voice data input,short time energy,spectral acnalysis,spectrogram,speech recognition,speech signal,voice recognition model,voice signal classification,voice signal recognition,zero crossing rate,Accuracy,Classification alg
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A computer vision approach for detection and counting of motorcycle riders in university campus
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contributor author | Waranusast, R. | |
contributor author | Timtong, V. | |
contributor author | Bundon, N. | |
contributor author | Tangnoi, C. | |
date accessioned | 2020-03-12T21:07:48Z | |
date available | 2020-03-12T21:07:48Z | |
date issued | 2014 | |
identifier other | 6925906.pdf | |
identifier uri | https://libsearch.um.ac.ir:443/fum/handle/fum/1038003 | |
format | general | |
language | English | |
publisher | IEEE | |
title | A computer vision approach for detection and counting of motorcycle riders in university campus | |
type | Conference Paper | |
contenttype | Metadata Only | |
identifier padid | 8164453 | |
subject keywords | cepstral analysis | |
subject keywords | signal classification | |
subject keywords | speech recognition | |
subject keywords | background noise | |
subject keywords | cepestral coefficient | |
subject keywords | feature vector | |
subject keywords | front end analysis | |
subject keywords | k-NN classification | |
subject keywords | k-nearest neighbor classification | |
subject keywords | mel frequency scale | |
subject keywords | pattern recognition model | |
subject keywords | pitch period | |
subject keywords | real-time voice data input | |
subject keywords | short time energy | |
subject keywords | spectral acnalysis | |
subject keywords | spectrogram | |
subject keywords | speech recognition | |
subject keywords | speech signal | |
subject keywords | voice recognition model | |
subject keywords | voice signal classification | |
subject keywords | voice signal recognition | |
subject keywords | zero crossing rate | |
subject keywords | Accuracy | |
subject keywords | Classification alg | |
identifier doi | 10.1109/CONFLUENCE.2014.6949338 | |
journal title | lectrical Engineering Congress (iEECON), 2014 International | |
filesize | 775262 | |
citations | 0 |