DVS Edition Citation

Abdullah, M. A., Ibrahim, M. A. R., Shapiee, M. N. A., Majeed, A. P. A., Razman, M. A. M., Musa, R. M. & Zakaria, M. A. (2020). The classification of skateboarding tricks by means of support vector machine: An evaluation of significant time-domain features. In M. Mohd Razman, J. Mat Jizat, N. Mat Yahya, H. Myung, A. Zainal Abidin & M. Abdul Karim (Hrsg.), Embracing Industry 4.0. Lecture Notes in Electrical Engineering, 678 (, S. 125-132). Singapore: Springer.

APA (7th ed.) Citation

Abdullah, M. A., Ibrahim, M. A. R., Shapiee, M. N. A., Majeed, A. P. A., Razman, M. A. M., Musa, R. M., & Zakaria, M. A. (2020). The classification of skateboarding tricks by means of support vector machine: An evaluation of significant time-domain features. Embracing Industry 4.0. Lecture Notes in Electrical Engineering, 678, 125-132.

Chicago Style (17th ed.) Citation

Abdullah, M. A., M. A. R. Ibrahim, M. N. A. Shapiee, A. P. A. Majeed, M. A. M. Razman, R. M. Musa, and M. A. Zakaria. "The Classification of Skateboarding Tricks by Means of Support Vector Machine: An Evaluation of Significant Time-domain Features." Embracing Industry 4.0. Lecture Notes in Electrical Engineering, 678 2020: 125-132.

MLA (9th ed.) Citation

Abdullah, M. A., et al. "The Classification of Skateboarding Tricks by Means of Support Vector Machine: An Evaluation of Significant Time-domain Features." Embracing Industry 4.0. Lecture Notes in Electrical Engineering, 678, 2020, pp. 125-132.