The classification of skateboarding tricks via transfer learning pipelines

• Main Authors: Abdullah, Muhammad Amirul, Ibrahim, Muhammad Ar Rahim, Shapiee, Muhammad Nur Aiman, Zakaria, Muhammad Aizzat, Razman, Mohd Azraai Mohd, Musa, Rabiu Muazu, Abu Osman, Noor Azuan, Majeed, Anwar P. P. Abdul
• Format: Article
• Published: PeerJ 2021
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://eprints.um.edu.my/34076/

This study aims at classifying flat ground tricks, namely Ollie, Kickflip, Shove-it, Nollie and Frontside 180, through the identification of significant input image transformation on different transfer learning models with optimized Support Vector Machine (SVM) classifier. A total of six amateur ska...