Search Results - Musa, R. M.

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  1. 1

    Machine learning analysis of intensity profiles and key indicators in standard microcycle of professional male soccer players

    Pillitteri, G., Musa, R. M., Clemente, F. M., Bongiovanni, T., Petrucci, M., Bianco, A., Beato, M., Battaglia, G.
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  2. 2

    Maschinelles Lernen im Hochleistungsskateboarding (Machine learning in high-performance skateboarding)

    Musa, R. M., Rasid, A. M. A., Samsudin, C. N. C., Majeed, A. P. P. A., Abdullah, M. R.
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  3. 3

    VAR consultation patterns and their association with fouls and misconduct: an analysis of the top five European football leagues

    Nazarudin, M. N., Abdul Majeed, A. P. P., Musa, R. M., Raj, N. B., Kuan, G., Abu Osman, N. A.
    Published in PLOS ONE (2025)
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  4. 4

    Associations between internal and external load parameters and match outcomes in men`s volleyball: a machine learning approach

    Lima, R. F., Musa, R. M., de Oliveira Castro, H., Clemente, F. M.
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  5. 5

    Test-retest reliability of customised inertial measurement units (IMUs) in evaluating skateboarding related manoeuvres

    Ab Rasid, A. M., Musa, A., Abdullah, M. A., Abdul Majeed, A. P. P., Mohd Razmaan, M. A., Abdullah, M. R., Abu Osman, N. A., Musa, R. M.
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  6. 6

    Personalized workload management in badminton using a machine learning model

    Musa, R. M., Abdul Majeed, A. P. P., Musawi Maliki, A. B. H., Kosni, N. A.
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  7. 7

    Comparing locomotor intensity indicators in soccer training and competition across contextual factors: a study of replaced coaches in a Portuguese professional 1st league team

    Sousa, H., Clemente, F. M., Sarmento, H., Gouveia, É. R., Musa, R. M.
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  8. 8

    Identification of high-performance volleyball players from anthropometric variables and psychological readiness: A machine-learning approach

    Musa, R. M., Abdul Majeed, A. P. P., Suhaimi, M. Z., Abdullah, M. R., Razman, M. A. M., Abdelhakim, D., Osman, N. A. A.
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  9. 9

    The classification of skateboarding tricks via transfer learning pipelines

    Abdullah, M. A., Ibrahim, M. A. R., Shapiee, M. N. A., Zakaria, M. A., Razman, M. A. M., Musa, R. M., Osman, N. A. A., Majeed, A. P. A.
    Published in PeerJ Computer Science (2021)
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  10. 10

    The classification of skateboarding tricks by means of support vector machine: An evaluation of significant time-domain features

    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.
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  11. 11

    The classification of skateboarding trick manoeuvres through the integration of IMU and machine learning

    Abdullah, M. A., Ibrahim, M. A. R., Shapiee, M. N. A., Razman, M. A. M., Musa, R. M., Majeed, A. P. A.
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  12. 12

    The classification of skateboarding trick manoeuvres: A K-nearest neighbour approach

    Ibrahim, M. A. R., Abdullah, M. A., Shapiee, M. N. A., Razman, M. A. M., Musa, R. M., Zakaria, M. A., Osman, N. A. A., Majeed, A. P. A.
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  13. 13

    The classification of skateboarding trick manoeuvres: A frequency-domain evaluation

    Ibrahim, M. A. R., Shapiee, M. N. A., Abdullah, M. A., Razman, M. A. M., Musa, R. M., Majeed, A. P. A.
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  14. 14

    Determining youth profile using principle component analysis for identifying talent in sports

    Mat-Rasid, S. M., Abdullah, M. R., Juahir, H., Maliki, A. B. H. M., Musa,R. M., Kosni, N. A., Hashim, M. R., EswaramoorthV., Najmi, N.
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