On the Establishment of E-referee for Sailing Ships Based on Deep Learning

Ying Ling, Jo-Hung Yu, Chih-Chien Shen, Chien-Hung Wu
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Abstract

The Taiwanese government is advocating the maritime activities of "Salute to the Sea". Nowadays, sailing is a popular leisure activity in Taiwan and it is also an Olympic event. Sailing competition is a large-scale competition, so it needs multiple referees and aerial photography to supervise. However, due to the large number of sailboats and the large range of activities, the need to supervise the audience through the referee is a big problem. This article builds on the basis of deep learning to build a sailing electronic referee. If there is a possibility that the sailboat may violate the rules by turning on the motor, this article will make a judgment and notify the referee. This article builds a system to help the referee's work, and uses the aerial shooting machine for compre-hensive shooting monitoring to facilitate the fairness of the sailing competition. From the experimental results, it can be known that the method proposed in this arti-cle is feasible, and the film can also be transmitted back to the platform for archiving.
基于深度学习的帆船电子裁判系统构建研究
台湾政府正在倡导“向海致敬”的海上活动。如今,帆船在台湾是一项很受欢迎的休闲活动,也是奥运会比赛项目。帆船比赛是一项大型比赛,需要多名裁判员和航拍进行监督。然而,由于帆船数量多,活动范围大,需要通过裁判员监督观众是一个大问题。本文在深度学习的基础上构建了一个帆船电子裁判。如果帆船有可能因启动电机而违反规则,本条将作出判断并通知裁判员。本文搭建了一个辅助裁判工作的系统,并利用航拍机进行全面的射击监控,以促进帆船比赛的公正性。从实验结果可以看出,本文提出的方法是可行的,并且可以将胶片传回平台进行存档。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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