AIMC Topic: Sports

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Advancing training effectiveness prediction in mass sport through longitudinal data: A mathematical model approach based on the Fitness-Fatigue Model.

PloS one
Despite the critical need for scientific training load assessment in mass sports, the Fitness-Fatigue Model (FFM) requires further mathematical optimization and practical output indicators. The aim of this study was to optimize the mathematical relat...

Deep learning for sports motion recognition with a high-precision framework for performance enhancement.

Scientific reports
Sports motion recognition is essential for performance analysis, injury prevention, and athlete monitoring. Traditional deep learning models, such as Long Short-Term Memory (LSTM) and Transformer-based architectures, struggle to capture motion dynami...

Machine learning-assisted triboelectric nanogenerator technology for intelligent sports.

Science advances
The rapid development of internet of things, big data, and artificial intelligence is propelling sports science into a data-driven era, demanding real-time, multidimensional athletic performance monitoring. Triboelectric nanogenerators (TENGs) have d...

Hierarchical query design and distributed attention in transformer for player group activity recognition in sports analysis.

Scientific reports
Group activity recognition in sports analysis is a critical challenge in computer vision, requiring robust modeling of complex player interactions and dynamic scenarios. Existing approaches predominantly rely on region-based features and two-stage pi...

Evaluation of sports teaching quality in universities based on fuzzy decision support system.

Scientific reports
Sports teaching in universities relies on staff experience, training modes., evaluated by the student's performance and competitive outcomes. The teaching quality assessment requires a large volume of data related to teaching patterns, training. A Te...

Internet of things enabled deep learning monitoring system for realtime performance metrics and athlete feedback in college sports.

Scientific reports
This study presents an Internet of Things (IoT)-enabled Deep Learning Monitoring (IoT-E-DLM) model for real-time Athletic Performance (AP) tracking and feedback in collegiate sports. The proposed work integrates advanced wearable sensor technologies ...

Predicting academic performance with fuzzy logic in prospective physical education and sports teachers.

Scientific reports
Numerous factors contribute to student success in educational settings, with academic support and learning strategies identified as key influences. Existing research highlights that various academic assistance and individual learning approaches shape...

Analysis of the mechanism of physical activity enhancing well-being among college students using artificial neural network.

Scientific reports
This study explores the impact mechanism of college students' sports behavior on their well-being by constructing an Artificial Neural Network (ANN) model. The study employs an ANN architecture that combines a Long Short-Term Memory (LSTM) network an...

Lightweight and efficient skeleton-based sports activity recognition with ASTM-Net.

PloS one
Human Activity Recognition (HAR) plays a pivotal role in video understanding, with applications ranging from surveillance to virtual reality. Skeletal data has emerged as a robust modality for HAR, overcoming challenges such as noisy backgrounds and ...

Team cognition (TC) in sport: Foundations, development, and performance implications.

Psychology of sport and exercise
This review synthesizes research on Team Cognition (TC) in sports, examining how these collective cognitive frameworks enable coordinated performance in high-stakes environments. TC facilitates team effectiveness by providing shared knowledge of task...