AIMC Topic: Soccer

Clear Filters Showing 1 to 10 of 48 articles

A method for feature division of Soccer Foul actions based on salience image semantics.

PloS one
The purpose of this study is to realize the automatic identification and classification of fouls in football matches and improve the overall identification accuracy. Therefore, a Deep Learning-Based Saliency Prediction Model (DLSPM) is proposed. DLSP...

Comparative analysis of automated foul detection in football using deep learning architectures.

Scientific reports
Automated foul detection in football represents a challenging task due to the dynamic nature of the game, the variability in player movements, and the ambiguity in differentiating fouls from regular physical contact. This study presents a comprehensi...

Deep learning-based recognition model of football player's technical action behavior using PCA-LBP algorithm.

Scientific reports
Football is a sport that requires sportsmen to have both physical strength and physical features. It must consider the distinctions between individuals and then provide targeted training. Football players can perform better on the field with targeted...

Subjective recovery in professional soccer players: A machine learning and mediation approach.

Journal of sports sciences
Coaches often ask players to judge their recovery status (subjective recovery). We aimed to explore potential determinants of subjective recovery in 101 male professional soccer players of 4 Italian Serie C teams and to further investigate whether th...

Artificial neural networks' estimations of lower-limb kinetics in sidestepping: Comparison of full-body vs. lower-body landmark sets.

Journal of biomechanics
Artificial neural networks (ANNs) offers potential for obtaining kinetics in non-laboratory. This study compared the estimation performance for ground reaction forces (GRF) and lower-limb joint moments during sidestepping between ANNs fed with full-b...

Use of AI methods to assessment of lower limb peak torque in deaf and hearing football players group.

Acta of bioengineering and biomechanics
Monitoring and assessing the level of lower limb motor skills using the Biodex System plays an important role in the training of football players and in post-traumatic rehabilitation. The aim of this study was to build and test an artificial intelli...

Predicting noncontact injuries of professional football players using machine learning.

PloS one
Noncontact injuries are prevalent among professional football players. Yet, most research on this topic is retrospective, focusing solely on statistical correlations between Global Positioning System (GPS) metrics and injury occurrence, overlooking t...

Prediction of talent selection in elite male youth soccer across 7 seasons: A machine-learning approach.

Journal of sports sciences
This study aimed to investigate the relative importance of parameters from several domains associated to both selecting or de-selecting players with regards to the next age group within a professional German youth soccer academy across a 7-year perio...

An Educational Review on Machine Learning: A SWOT Analysis for Implementing Machine Learning Techniques in Football.

International journal of sports physiology and performance
PURPOSE: The abundance of data in football presents both opportunities and challenges for decision making. Consequently, this review has 2 primary objectives: first, to provide practitioners with a concise overview of the characteristics of machine-l...

Prediction of Perceived Exertion Ratings in National Level Soccer Players Using Wearable Sensor Data and Machine Learning Techniques.

Journal of sports science & medicine
This study aimed to identify relationships between external and internal load parameters with subjective ratings of perceived exertion (RPE). Consecutively, these relationships shall be used to evaluate different machine learning models and design a ...