Generating context-specific sports training plans by combining generative adversarial networks.
Personalized sports training plans are essential for addressing individual athlete needs, but traditional methods often need to integrate diverse data types, limiting adaptability and effectiveness. Existing machine learning (ML) and rule-based approaches cannot dynamically generate context-specific...
Saved in:
Main Authors: | Juquan Tan, Jingwen Chen |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2025-01-01
|
Series: | PLoS ONE |
Online Access: | https://doi.org/10.1371/journal.pone.0318321 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Research Developments in Generative Adversarial Networks for Image Restoration and Communication
by: Zhou Peng
Published: (2025-01-01) -
Prediksi Penuaan Wajah Manusia Berbasis Generative Adversarial Network
by: Beladina Elfitri, et al.
Published: (2024-02-01) -
Stock price prediction with attentive temporal convolution-based generative adversarial network
by: Ying Liu, et al.
Published: (2025-03-01) -
DragGAN: Interactive Point-Based Image Manipulation on Generative Adversarial Networks
by: Wu Muran
Published: (2025-01-01) -
Diffused Multi-scale Generative Adversarial Network for low-dose PET images reconstruction
by: Xiang Yu, et al.
Published: (2025-02-01)