Name
Title | ||
|---|---|---|
Research of the performance improvement in traffic accident detecting system within the cross road |
Abstract | ||
|---|---|---|
The pu pose of thzs paper 1s to develop znczdent detectzon akgorzthm for zmpmvzng pep-formance ofthe automated trafJic acczdent recoder zn operatzon zn Korea from 2004. The current automated traflc acczdent coder has pmbkems zn Increase of detectzon rate(DR1 and co r ~ cdte tectzon rate(CDR1 that aR sensztzve to envzronnaentak znfluences a s hme elapsed. In order to solve these pmbkems, we dmekoped the zmproved akgorzthms by utzkmng ojfthe object recognztzon gmnt of wezght and fluzd approxzmahon akgorzthm, the remkt ofjekd test for 2 weeks amounted to 28 detectzons ofthe movze jkes, totak numbers of real traflc acczdents was 6 cases zn the detectzon area durzng the evakuatzon peaod. As the test was 100% of detectzon rate(DR1, 21.4% of correct detectzon rate(CDR1, we learned the system was zmpmved the pep-formance than exzshng system(DR 66.7% CDR 2.03 %I. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/MUE.2007.182 | MUE |
Keywords | Field | DocType |
current automated traflc acczdent,real traflc acczdents,cross road,remkt ofjekd test,fluzd approxzmahon akgorzthm,detectzon area durzng,performance improvement,znczdent detectzon akgorzthm,correct detectzon rate,cdte tectzon rate,exzshng system,traffic accident,detectzon rate,object recognition,frequency,pixel,system testing | Approximation algorithm,Object detection,Cd recording,System testing,Simulation,Computer science,Traffic accident,Pixel,Performance improvement,Cognitive neuroscience of visual object recognition | Conference |
ISBN | Citations | PageRank |
0-7695-2777-9 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sungjun YOO | 1 | 0 | 0.34 |
| Youngchan Kim | 2 | 31 | 4.82 |
| DongYoung Lee | 3 | 1 | 1.03 |