AIMC Topic: Football

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Deep Learning-Based Football Player Detection in Videos.

Computational intelligence and neuroscience
The main task of football video analysis is to detect and track players. In this work, we propose a deep convolutional neural network-based football video analysis algorithm. This algorithm aims to detect the football player in real time. First, five...

Influence of Different Passing Methods of Physical Fitness in Football Using Deep Learning.

Computational intelligence and neuroscience
Deep learning is a new direction in the field of machine learning, which learns the inherent laws and levels of data sample representation. The information gained during learning plays an important role in interpreting data such as text, images, and ...

Football Game Video Analysis Method with Deep Learning.

Computational intelligence and neuroscience
Football is a beloved sport, and its wide audience makes football video one of the most analytically valuable types of video. Researchers have achieved certain research results in football video content analysis. How to locate interesting event clips...

Automated soccer head impact exposure tracking using video and deep learning.

Scientific reports
Head impacts are highly prevalent in sports and there is a pressing need to investigate the potential link between head impact exposure and brain injury risk. Wearable impact sensors and manual video analysis have been utilized to collect impact expo...

Evaluation of the Quality of Football Teaching in Colleges and Universities Based on Artificial Neural Networks.

Computational intelligence and neuroscience
Every country is developing under the concept of artificial intelligence. Many countries are already working on student monitoring systems that allow them to control the student's mentality and analyze each student's behavior with the help of a wirel...

Rapid Estimation of Entire Brain Strain Using Deep Learning Models.

IEEE transactions on bio-medical engineering
OBJECTIVE: Many recent studies suggest that brain deformation resulting from head impacts are linked to the corresponding clinical outcome, such as mild traumatic brain injury (mTBI). Even if several finite element (FE) head models have been develope...

From the Laboratory to the Field: IMU-Based Shot and Pass Detection in Football Training and Game Scenarios Using Deep Learning.

Sensors (Basel, Switzerland)
The applicability of sensor-based human activity recognition in sports has been repeatedly shown for laboratory settings. However, the transferability to real-world scenarios cannot be granted due to limitations on data and evaluation methods. On the...

Analysing the predictive capacity and dose-response of wellness in load monitoring.

Journal of sports sciences
This study aimed to identify the predictive capacity of wellness questionnaires on measures of training load using machine learning methods. The distributions of, and dose-response between, wellness and other load measures were also examined, offerin...

Relationship between training load and recovery in collegiate American football players during pre-season training.

Science & medicine in football
: The purpose of this study was to examine the relationship between training load and next-day recovery in collegiate American football (AF) players during pre-season.: Seventeen athletes (Linemen, n = 6; Non-linemen, n = 11) participated in the 14-d...

Instantaneous Whole-Brain Strain Estimation in Dynamic Head Impact.

Journal of neurotrauma
Head injury models are notoriously time consuming and resource demanding in simulations, which prevents routine application. Here, we extend a convolutional neural network (CNN) to instantly estimate element-wise distribution of peak maximum principa...