Performance comparison between SVM and K-Means for vehicle counting
Support vector machine (SVM) and K-means have been two well known methods used in classification. Choosing an accurate classifier for good features to differentiate between the foreground and background has a significant effect in increasing the accuracy of the detection. This paper presents and ana...
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2020
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my.utm.912372021-06-30T11:59:25Z http://eprints.utm.my/id/eprint/91237/ Performance comparison between SVM and K-Means for vehicle counting El-Khoreby, Mohamed A. Abu Bakar, Syed Abd. Rahman Mohd. Mokji, Musa Omar, Syaril Nizam TK Electrical engineering. Electronics Nuclear engineering Support vector machine (SVM) and K-means have been two well known methods used in classification. Choosing an accurate classifier for good features to differentiate between the foreground and background has a significant effect in increasing the accuracy of the detection. This paper presents and analyzes performance comparison between SVM and K-means classifiers for vehicle counting targeted for intelligence transportation systems (ITS) application. In particular, precision and recall have been used for the comparison between the two methods. Five videos from different weather conditions have been used for the testing purposes. SVM shows a better performance in terms of precision and recall. 2020-07-20 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/91237/1/SyedAbdRahman2020_PerformanceComparisonBetweenSVMandK-Means.pdf El-Khoreby, Mohamed A. and Abu Bakar, Syed Abd. Rahman and Mohd. Mokji, Musa and Omar, Syaril Nizam (2020) Performance comparison between SVM and K-Means for vehicle counting. In: 2019 Sustainable and Integrated Engineering International Conference, SIE 2019, 8 December 2019 - 9 December 2019, The Everly Hotel, Putrajaya, Malaysia. http://dx.doi.org/10.1088/1757-899X/884/1/012077 |
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TK Electrical engineering. Electronics Nuclear engineering |
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TK Electrical engineering. Electronics Nuclear engineering El-Khoreby, Mohamed A. Abu Bakar, Syed Abd. Rahman Mohd. Mokji, Musa Omar, Syaril Nizam Performance comparison between SVM and K-Means for vehicle counting |
| description |
Support vector machine (SVM) and K-means have been two well known methods used in classification. Choosing an accurate classifier for good features to differentiate between the foreground and background has a significant effect in increasing the accuracy of the detection. This paper presents and analyzes performance comparison between SVM and K-means classifiers for vehicle counting targeted for intelligence transportation systems (ITS) application. In particular, precision and recall have been used for the comparison between the two methods. Five videos from different weather conditions have been used for the testing purposes. SVM shows a better performance in terms of precision and recall. |
| format |
Conference or Workshop Item |
| author |
El-Khoreby, Mohamed A. Abu Bakar, Syed Abd. Rahman Mohd. Mokji, Musa Omar, Syaril Nizam |
| author_facet |
El-Khoreby, Mohamed A. Abu Bakar, Syed Abd. Rahman Mohd. Mokji, Musa Omar, Syaril Nizam |
| author_sort |
El-Khoreby, Mohamed A. |
| title |
Performance comparison between SVM and K-Means for vehicle counting |
| title_short |
Performance comparison between SVM and K-Means for vehicle counting |
| title_full |
Performance comparison between SVM and K-Means for vehicle counting |
| title_fullStr |
Performance comparison between SVM and K-Means for vehicle counting |
| title_full_unstemmed |
Performance comparison between SVM and K-Means for vehicle counting |
| title_sort |
performance comparison between svm and k-means for vehicle counting |
| publishDate |
2020 |
| url |
http://eprints.utm.my/id/eprint/91237/1/SyedAbdRahman2020_PerformanceComparisonBetweenSVMandK-Means.pdf http://eprints.utm.my/id/eprint/91237/ http://dx.doi.org/10.1088/1757-899X/884/1/012077 |
| _version_ |
1705056685033259008 |
| score |
13.250345 |