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- W3093597704 abstract "Athletes can still insist on the practicality of sports practice in today's sports environment by locating image detection technology, video and video files, as well as broadcast data detection key format. However, from the most advanced of the situation in the country, goal can confirm that the light detection dong area is still immature. So let's take a look at the video cloth applied to detect motion pictures in ages to search for software. Method are looking at the side of detection, grayscale processing, grasping the project, target identification, and see the light detection era. The actual sports programs and the desire to meet the different needs of the sports image detection mix. At the same time, in the present study, found that the popularity of athletes and judge, motion recognition of motor behavior. Along with affirmed the effectiveness of this method of research, have created a platform for inspection. Results show that the research method is always practical, can provide a theoretical basis for future research. A set of rules contained in a hierarchy: First, the Particle Swarm Optimize [PSO] algorithm is used to the annotation image per day. In the experiment, 3 sets of data were used to evaluate a set of rules, the results show that the performance of the algorithm." @default.
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- W3093597704 date "2021-02-01" @default.
- W3093597704 modified "2023-10-14" @default.
- W3093597704 title "Sports image detection based on particle swarm optimization algorithm" @default.
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- W3093597704 doi "https://doi.org/10.1016/j.micpro.2020.103345" @default.
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