In order to realize high-accuracy recognition of aerobics actions, a highly applicable deep learning model and faster data processing methods are required. Therefore, it is a major difficulty in the field of research on aerobics action recognition. Based on this, this paper studies the application of the convolution neural network (CNN) model combined with the pyramid algorithm in aerobics action recognition. Firstly, the basic architecture of the convolution neural network model based on the pyramid algorithm is proposed. Combined with the application strategy of the common recognition model in aerobics action recognition, the traditional aerobics action capture information is processed. Through the characteristics of different aerobics actions, different accurate recognition is realized, and then, the error of the recognition model is evaluated. Secondly, the composite recognition function of the convolution neural network model in this application is constructed, and the common data layer effect recognition method is used in the optimization recognition. Aiming at the shortcomings of the composite recognition function, the pyramid algorithm is used to improve the convolution neural network recognition model by deep learning optimization. Finally, through the effectiveness comparison experiment, the results show that the convolution neural network model based on the pyramid algorithm is more efficient than the conventional recognition method in aerobics action recognition.

中文翻译：

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卷积神经网络（CNN）模型结合金字塔算法在健美操动作识别中的应用

为了实现健美操动作的高精度识别，需要高度适用的深度学习模型和更快的数据处理方法。因此，是健美操动作识别研究领域的一大难点。基于此，本文研究了卷积神经网络（CNN）模型结合金字塔算法在健美操动作识别中的应用。首先，提出了基于金字塔算法的卷积神经网络模型的基本架构。结合通用识别模型在健美操动作识别中的应用策略，对传统健美操动作捕捉信息进行处理。通过不同健美操动作的特点，实现不同的精准识别，进而评估识别模型的误差。其次，构建了本申请中卷积神经网络模型的复合识别函数，在优化识别中采用了常用的数据层效应识别方法。针对复合识别函数的不足，采用金字塔算法通过深度学习优化改进卷积神经网络识别模型。最后，通过有效性对比实验，结果表明基于金字塔算法的卷积神经网络模型在健美操动作识别方面比传统的识别方法更高效。针对复合识别函数的不足，采用金字塔算法通过深度学习优化改进卷积神经网络识别模型。最后，通过有效性对比实验，结果表明基于金字塔算法的卷积神经网络模型在健美操动作识别方面比传统的识别方法更高效。针对复合识别函数的不足，采用金字塔算法通过深度学习优化改进卷积神经网络识别模型。最后，通过有效性对比实验，结果表明基于金字塔算法的卷积神经网络模型在健美操动作识别方面比传统的识别方法更高效。