AIMC Topic: Football

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Detection of violence in football sport based on deep learning and optimization algorithm.

Scientific reports
Among the various sports activities that are carried out all over the world, football is undoubtedly the most popular, most participated in and most watched activity and sport. The increasing spread of sports has caused it to break down geographical,...

SHAP-based interpretable machine learning for injury risk prediction in university football players: a multi-dimensional data analysis approach.

Scientific reports
Sports injury prediction is crucial for university football player health, yet existing research predominantly focuses on professional athletes and lacks interpretability. Using the Kaggle "University Football Injury Prediction Dataset" (800 Chinese ...

Football sports automatic judgment model based on improved YOLOv7 and RNN.

PloS one
The extraction, classification, and judgment of sports video scenes can improve work efficiency and accuracy. To understand sports videos in dynamic scenes, this study applies deep learning technology, firstly introducing clustering algorithm and att...

A deep learning algorithm for automatic 3D segmentation and quantification of hamstrings musculotendon injury from MRI.

Scientific reports
In high-velocity sports, hamstring strain injuries are common causes of missed play and have high rates of reinjury. Evaluating the severity and location of a hamstring strain injury, currently graded by a clinician using a semiqualitative muscle inj...

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...

Machine learning model to study the rugby head impact in a laboratory setting.

PloS one
The incidence of head impacts in rugby has been a growing concern for player safety. While rugby headgear shows potential to mitigate head impact intensity during laboratory simulations, evaluating its on-field effectiveness is challenging. Current r...

AI-Based Denoising of Head Impact Kinematics Measurements With Convolutional Neural Network for Traumatic Brain Injury Prediction.

IEEE transactions on bio-medical engineering
OBJECTIVE: Wearable devices are developed to measure head impact kinematics but are intrinsically noisy because of the imperfect interface with human bodies. This study aimed to improve the head impact kinematics measurements obtained from instrument...

Brain Deformation Estimation With Transfer Learning for Head Impact Datasets Across Impact Types.

IEEE transactions on bio-medical engineering
OBJECTIVE: The machine-learning head model (MLHM) to accelerate the calculation of brain strain and strain rate, which are the predictors for traumatic brain injury (TBI), but the model accuracy was found to decrease sharply when the training/test da...

The Impact of Drop Test Conditions on Brain Strain Location and Severity: A Novel Approach Using a Deep Learning Model.

Annals of biomedical engineering
In contact sports such as rugby, players are at risk of sustaining traumatic brain injuries (TBI) due to high-intensity head impacts that generate high linear and rotational accelerations of the head. Previous studies have established a clear link be...

Research on Video Target Detection and Tracking in Football Matches.

Computational intelligence and neuroscience
Computer vision is an interesting branch of artificial intelligence which is dedicated to how electronic devices can achieve the level of capabilities to perceive things just like ordinary human beings do. In order to solve the poor effect of video f...