The classification of skateboarding tricks via transfer learning pipelines

The classification of skateboarding tricks via transfer learning pipelines

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...

Full description

Saved in:
Bibliographic Details
Main Authors: Muhammad Amirul, Abdullah, Muhammad Ar Rahim, Ibrahim, Muhammad Nur Aiman, Shapiee, Muhammad Aizzat, Zakaria, Mohd Azraai, Mohd Razman, Rabiu Muazu, Musa, Noor Azuan, Abu Osman, Anwar P.P., Abdul Majeed
Format: Article
Language:en
Published: Peerj Inc. 2021
Subjects:
TJ Mechanical engineering and machinery
Online Access:http://umpir.ump.edu.my/id/eprint/32628/1/JOURNAL%20%281%29%20-%20The%20classification%20of%20skateboarding%20tricks%20via%20transfer%20learning%20pipelines%20%281%29.pdf
http://umpir.ump.edu.my/id/eprint/32628/
https://peerj.com/articles/cs-680/
http:10.7717/peerj-cs.680
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

http://umpir.ump.edu.my/id/eprint/32628/1/JOURNAL%20%281%29%20-%20The%20classification%20of%20skateboarding%20tricks%20via%20transfer%20learning%20pipelines%20%281%29.pdf
http://umpir.ump.edu.my/id/eprint/32628/
https://peerj.com/articles/cs-680/
http:10.7717/peerj-cs.680

Similar Items