Computational intelligence and neuroscience
Jul 12, 2022
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...
Computational intelligence and neuroscience
Jun 25, 2022
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 ...
Computational intelligence and neuroscience
Jun 8, 2022
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...
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...
Computational intelligence and neuroscience
May 27, 2022
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...
IEEE transactions on bio-medical engineering
Oct 19, 2021
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...
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...
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...
: 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...
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...
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