This paper focuses on the theme of the application of deep learning in the field of basketball sports, using research methods such as literature research, video analysis, comparative research, and mathematical statistics to explore deep learning in real-time analysis of basketball sports data. The basketball posture action recognition and analysis system proposed for basketball movement is composed of two parts serially. The first part is based on the bottom-up posture estimation method to locate the joint points and is used to extract the posture sequence of the target in the video. The second part is the analysis and research of the action recognition algorithm based on the convolution of the space-time graph. According to the extracted posture sequence, the basketball action of the set classification is recognized. In order to obtain more accurate and three-dimensional information, a multitraining target method can be used in training; that is, multiple indicators can be detected and feedback is provided at the same time to correct player errors in time; the other is an auxiliary method, which is compared with ordinary training. The method can actively correct technical movements, train players to form muscle memory, and improve their abilities. Through the research of this article, it provides a theoretical basis for promoting the application of deep learning in the field of basketball and also provides a theoretical reference for the wider application of deep learning in the field of sports. At the same time, the designed real-time analysis system of basketball data also provides more actual reference values for coaches and athletes.

中文翻译：

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基于深度学习的篮球运动数据实时分析

本文以篮球研究领域的深度学习为主题，通过文献研究，视频分析，比较研究和数学统计等研究方法，探索深度学习在篮球运动数据实时分析中的应用。为篮球运动提出的篮球姿势动作识别与分析系统由两部分组成。第一部分基于自下而上的姿势估计方法来定位关节点，并用于提取视频中目标的姿势序列。第二部分是基于时空图卷积的动作识别算法的分析与研究。根据提取的姿势序列，识别出类别分类的篮球动作。为了获得更准确的三维信息，可以在训练中采用多目标训练方法。也就是说，可以检测到多个指示符并同时提供反馈以及时纠正玩家错误；另一种是辅助方法，与普通训练相比。该方法可以积极地纠正技术动作，训练运动员形成肌肉记忆，并提高他们的能力。通过本文的研究，为促进深度学习在篮球领域的应用提供了理论依据，也为深度学习在体育领域的广泛应用提供了理论参考。同时，设计的篮球数据实时分析系统还为教练和运动员提供了更多的实际参考值。