The Classification of Skateboarding Tricks by Means of the Integration of Transfer Learning and Machine Learning Models-Reference-Cited by-同舟云学术

The Classification of Skateboarding Tricks by Means of the Integration of Transfer Learning and Machine Learning Models

Published:2020 Issue: Volume: Page:219-226
ISSN:1876-1100
Container-title:Embracing Industry 4.0
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Author:

Shapiee Muhammad Nur Aiman^ORCID,Ibrahim Muhammad Ar Rahim,Razman Mohd Azraai Mohd,Abdullah Muhammad Amirul,Musa Rabiu Muazu,Abdul Majeed Anwar P. P.^ORCID

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-15-6025-5_20

Reference12 articles.

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2. Chen Y, Xue Y (2015) A deep learning approach to human activity recognition based on single accelerometer. In: 2015 IEEE international conference on systems, man, and cybernetics, pp 1488–1492. https://doi.org/10.1109/SMC.2015.263

3. Park JH, Park SU, Uddin MZ, Al-Antari MA, Al-Masni MA, Kim T-S (2017) A single depth sensor based human activity recognition via convolutional neural network. In: International conference on the development of biomedical engineering in Vietnam. Springer, Berlin, pp 541–545

4. Sargano AB, Wang X, Angelov P, Habib Z (2017) Human action recognition using transfer learning with deep representations. In: 2017 international joint conference on neural networks (IJCNN), pp 463–469. https://doi.org/10.1109/IJCNN.2017.7965890

5. Groh BH, Fleckenstein M, Kautz T, Eskofier BM (2017) Classification and visualization of skateboard tricks using wearable sensors. Pervasive Mob Comput 40:42–55. https://doi.org/10.1016/j.pmcj.2017.05.007

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