AIMC Topic: Basketball

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A Classification Method for Thoracolumbar Vertebral Fractures due to Basketball Sports Injury Based on Deep Learning.

Computational and mathematical methods in medicine
OBJECTIVE: There are more and more basketball competitions, to propose a classification method of thoracolumbar fractures to assist in the diagnosis of basketball injuries, to analyze the feasibility of its clinical application, and to improve the re...

Development Status and Influencing Factors of Competitive Basketball Management System under the Background of Deep Learning.

Computational intelligence and neuroscience
Competitive basketball is one of the most popular sports in the world. With the development of China's sports power strategy, the national movement has strengthened the status of basketball in sports. However, China's competitive basketball ranking i...

Deep Learning Algorithm-Based Target Detection and Fine Localization of Technical Features in Basketball.

Computational intelligence and neuroscience
Based on SSD to detect players, a super-pixel-based FCN-CNN player segmentation algorithm is proposed to filter out the complex background around players, which is more conducive to the subsequent pose estimation for target detection and fine localiz...

Analysis of Basketball Technical Movements Based on Human-Computer Interaction with Deep Learning.

Computational intelligence and neuroscience
With the continuous development of computer technology, analysis techniques based on various types of sports data sets are also evolving. One typical representative is image-based motion recognition technology, which enables video action recognition ...

Video Analysis and System Construction of Basketball Game by Lightweight Deep Learning under the Internet of Things.

Computational intelligence and neuroscience
With the explosive growth of sports video data on the internet platform, how to scientifically manage this information has become a major challenge in the current big data era. In this context, a new lightweight player segmentation algorithm is propo...

Application of Unsupervised Migration Method Based on Deep Learning Model in Basketball Training.

Computational intelligence and neuroscience
Nowadays, China's sports industry has attained effective development, but the athlete's efficiency in the training process is too complex to have a scientific guarantee. Machine learning technology's help in guiding the sports training process has be...

Optimization Research on Deep Learning and Temporal Segmentation Algorithm of Video Shot in Basketball Games.

Computational intelligence and neuroscience
The analysis of the video shot in basketball games and the edge detection of the video shot are the most active and rapid development topics in the field of multimedia research in the world. Video shots' temporal segmentation is based on video image ...

Basketball Activity Classification Based on Upper Body Kinematics and Dynamic Time Warping.

International journal of sports medicine
Basketball activity classification can help document players' statistics, allow coaches, trainers and the medical team to quantitatively supervise players' physical exertion and optimize training strategy, and further help prevent potential injuries....

A Method for Using Player Tracking Data in Basketball to Learn Player Skills and Predict Team Performance.

PloS one
Player tracking data represents a revolutionary new data source for basketball analysis, in which essentially every aspect of a player's performance is tracked and can be analyzed numerically. We suggest a way by which this data set, when coupled wit...

Detecting tactical patterns in basketball: comparison of merge self-organising maps and dynamic controlled neural networks.

European journal of sport science
The soaring amount of data, especially spatial-temporal data, recorded in recent years demands for advanced analysis methods. Neural networks derived from self-organizing maps established themselves as a useful tool to analyse static and temporal dat...