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Number of items: 9.

Aina Munirah, Ab Rasid and Rabiu Muazu, Musa and Abdul Majeed, Anwar P. P. and Maliki, Ahmad Bisyri Husin Musawi and Mohamad Razali, Abdullah and Mohd Azraai, Mohd Razman and Noor Azuan, Abu Osman (2024) Physical fitness and motor ability parameters as predictors for skateboarding performance: A logistic regression modelling analysis. PLoS ONE, 19 (e0296467). pp. 1-16. ISSN 1932-6203. (Published)

Aina Munirah, Ab Rasid and Muhammad Zuhaili, Suhaimi and Anwar, P. P. Abdul Majeed and Mohd Azraai, Mohd Razman and Mohd Hasnun Ariff, Hassan and Nasree, Najmi and Noor Azuan, Abu Osman and Rabiu Muazu, Musa (2023) A cluster analysis and artificial neural network of identifying skateboarding talents based on bio-fitness indicators. In: Innovation and Technology in Sports. Lecture Notes in Bioengineering; International Conference on Innovation and Technology in Sports, ICITS 2022 , 14 - 15 November 2022 , Kuala Lumpur. 47 -56.. ISSN 2195-271X ISBN 978-981990296-5 (Published)

Muhammad Amirul, Abdullah and Muhammad Ar Rahim, Ibrahim and Muhammad Nur Aiman, Shapiee and Mohd Azraai, Mohd Razman and Rabiu Muazu, Musa and Noor Azuan, Abu Osman and Muhammad Aizzat, Zakaria and Anwar, P. P. Abdul Majeed (2023) An evaluation of different input transformation for the classification of skateboarding tricks by means of transfer learning. In: Lecture Notes in Bioengineering; International Conference on Innovation and Technology in Sports, ICITS 2022 , 14 - 15 November 2022 , Kuala Lumpur. 269 -275.. ISSN 2195-271X ISBN 978-981990296-5 (Published)

Rabiu Muazu, Musa and Isyaku, Hassan and Mohamad Razali, Abdullah and Mohd Nazri, Latiff Azmi and Abdul Majeed, Anwar P. P. and Noor Azuan, Abu Osman (2022) A longitudinal analysis of injury characteristics among elite and amateur tennis players at different tournaments from electronic newspaper reports. Frontiers in Public Health, 10 (835119). pp. 1-14. ISSN 2296-2565. (Published)

Muhammad Nur Aiman, Shapiee and Muhammad Ar Rahim, Ibrahim and Mohd Azraai, Mohd Razman and Muhammad Amirul, Abdullah and Musa, Rabiu Muazu and Noor Azuan, Abu Osman and P.P. Abdul Majeed, Anwar (2022) The classification of skateboarding tricks by means of the integration of transfer learning models and K-Nearest neighbors. In: Lecture Notes in Electrical Engineering. Innovative Manufacturing, Mechatronics and Materials Forum, iM3F 2020 , 6 August 2020 , Gambang. pp. 439-450., 730. ISSN 1876-1100 ISBN 978-981334596-6 (Published)

Musa, Rabiu Muazu and Hassan, Isyaku and Mohamad Razali, Abdullah and Mohd Nazri Latiff, Azmi and Abdul Majeed, Anwar P. P. and Noor Azuan, Abu Osman (2021) Surveillance of injury types, locations, and intensities in male and female tennis players: A content analysis of online newspaper reports. International Journal of Environmental Research and Public Health, 18 (23). pp. 1-10. ISSN 1661-7827. (Published)

Muhammad Amirul, Abdullah and Muhammad Ar Rahim, Ibrahim and Muhammad Nur Aiman, Shapiee and Muhammad Aizzat, Zakaria and Mohd Azraai, Mohd Razman and Rabiu Muazu, Musa and Noor Azuan, Abu Osman and Anwar P.P., Abdul Majeed (2021) The classification of skateboarding tricks via transfer learning pipelines. PeerJ Computer Science. pp. 1-18. ISSN 2376-5992. (Published)

Muhammad Nur Aiman, Shapiee and Muhammad Ar Rahim, Ibrahim and Muhammad Amirul, Abdullah and Rabiu Muazu, Musa and Noor Azuan, Abu Osman and Anwar P. P., Abdul Majeed and Mohd Azraai, Mohd Razman (2020) The classification of skateboarding tricks : A transfer learning and machine learning approach. Mekatronika - Journal of Intelligent Manufacturing & Mechatronics, 2 (2). pp. 1-12. ISSN 2637-0883. (Published)

Muhammad Ar Rahim, Ibrahim and Muhammad Amirul, Abdullah and Muhammad Nur Aiman, Shapiee and Mohd Azraai, Mohd Razman and Rabiu Muazu, Musa and Muhammad Aizzat, Zakaria and Noor Azuan, Abu Osman and Anwar P. P., Abdul Majeed The classification of skateboarding trick manoeuvres: A K-nearest neighbour approach. Lecture Notes in Bioengineering. (Published)

This list was generated on Thu Nov 21 21:31:10 2024 +08.