An evaluation of different input transformation for the classification of skateboarding tricks by means of transfer learning
This study aims to investigate the effect of different input images, namely raw data (RAW) and Continuous Wavelet Transform (CWT) towards the discriminating of street skateboarding tricks, i.e., Ollie, Kickflip, Shove-it, Nollie and Frontside 180 through a variety of transfer learning with optimised...
| Main Authors: | , , , , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
Springer
2023
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/39755/ http://umpir.ump.edu.my/id/eprint/39755/1/An%20evaluation%20of%20different%20input%20transformation%20for%20the%20classification%20of%20skateboarding%20.pdf |
| _version_ | 1848825857866465280 |
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| author | Muhammad Amirul, Abdullah Muhammad Ar Rahim, Ibrahim Muhammad Nur Aiman, Shapiee Mohd Azraai, Mohd Razman Rabiu Muazu, Musa Noor Azuan, Abu Osman Muhammad Aizzat, Zakaria Anwar, P. P. Abdul Majeed |
| author_facet | Muhammad Amirul, Abdullah Muhammad Ar Rahim, Ibrahim Muhammad Nur Aiman, Shapiee Mohd Azraai, Mohd Razman Rabiu Muazu, Musa Noor Azuan, Abu Osman Muhammad Aizzat, Zakaria Anwar, P. P. Abdul Majeed |
| author_sort | Muhammad Amirul, Abdullah |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | This study aims to investigate the effect of different input images, namely raw data (RAW) and Continuous Wavelet Transform (CWT) towards the discriminating of street skateboarding tricks, i.e., Ollie, Kickflip, Shove-it, Nollie and Frontside 180 through a variety of transfer learning with optimised k-Nearest Neighbors (kNN) pipelines. Six amateur skateboarders participated in the study, executed the aforesaid tricks five times per trick on an instrumented skateboard where six time-domain signals were extracted prior it was transformed to RAW and CWT. It was shown from the study that the CWT-InceptionV3-optimised kNN pipeline could attain an average test and validation accuracy of 90%. |
| first_indexed | 2025-11-15T03:35:36Z |
| format | Conference or Workshop Item |
| id | ump-39755 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T03:35:36Z |
| publishDate | 2023 |
| publisher | Springer |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-397552023-12-26T03:55:03Z http://umpir.ump.edu.my/id/eprint/39755/ An evaluation of different input transformation for the classification of skateboarding tricks by means of transfer learning Muhammad Amirul, Abdullah Muhammad Ar Rahim, Ibrahim Muhammad Nur Aiman, Shapiee Mohd Azraai, Mohd Razman Rabiu Muazu, Musa Noor Azuan, Abu Osman Muhammad Aizzat, Zakaria Anwar, P. P. Abdul Majeed GV Recreation Leisure Q Science (General) TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery This study aims to investigate the effect of different input images, namely raw data (RAW) and Continuous Wavelet Transform (CWT) towards the discriminating of street skateboarding tricks, i.e., Ollie, Kickflip, Shove-it, Nollie and Frontside 180 through a variety of transfer learning with optimised k-Nearest Neighbors (kNN) pipelines. Six amateur skateboarders participated in the study, executed the aforesaid tricks five times per trick on an instrumented skateboard where six time-domain signals were extracted prior it was transformed to RAW and CWT. It was shown from the study that the CWT-InceptionV3-optimised kNN pipeline could attain an average test and validation accuracy of 90%. Springer 2023 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/39755/1/An%20evaluation%20of%20different%20input%20transformation%20for%20the%20classification%20of%20skateboarding%20.pdf 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) https://doi.org/10.1007/978-981-99-0297-2_22 |
| spellingShingle | GV Recreation Leisure Q Science (General) TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery Muhammad Amirul, Abdullah Muhammad Ar Rahim, Ibrahim Muhammad Nur Aiman, Shapiee Mohd Azraai, Mohd Razman Rabiu Muazu, Musa Noor Azuan, Abu Osman Muhammad Aizzat, Zakaria Anwar, P. P. Abdul Majeed An evaluation of different input transformation for the classification of skateboarding tricks by means of transfer learning |
| title | An evaluation of different input transformation for the classification of skateboarding tricks by means of transfer learning |
| title_full | An evaluation of different input transformation for the classification of skateboarding tricks by means of transfer learning |
| title_fullStr | An evaluation of different input transformation for the classification of skateboarding tricks by means of transfer learning |
| title_full_unstemmed | An evaluation of different input transformation for the classification of skateboarding tricks by means of transfer learning |
| title_short | An evaluation of different input transformation for the classification of skateboarding tricks by means of transfer learning |
| title_sort | evaluation of different input transformation for the classification of skateboarding tricks by means of transfer learning |
| topic | GV Recreation Leisure Q Science (General) TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery |
| url | http://umpir.ump.edu.my/id/eprint/39755/ http://umpir.ump.edu.my/id/eprint/39755/ http://umpir.ump.edu.my/id/eprint/39755/1/An%20evaluation%20of%20different%20input%20transformation%20for%20the%20classification%20of%20skateboarding%20.pdf |