| Autor: |
Srinivasulu, K., Premkumar, S. |
| Předmět: |
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| Zdroj: |
AIP Conference Proceedings; 2024, Vol. 2853 Issue 1, p1-8, 8p |
| Abstrakt: |
The purpose of this study is to use second derivative to forecast traffic photos using EigenVector level based edge detection and to compare this to the more traditional first derivative technique. From the UCI archive, we pull a total of 52 samples. The acquired data is split into two sets, one for training purposes (n=26) and another for actual use (n=26). Clincalc is used for G power analysis in order to determine the necessary sample size. There are two sections: the alpha (0.05) and power (80 percent). Results from using the suggested model show that its second derivative approach is more accurate (88%) and more sensitive (84%), on average, than the first derivative approach (85% accurate, 82% sensitive). An insignificant value of 0.000 was calculated. It may be concluded that the second derivative approach has a far higher detection rate than the first derivative method. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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