School of Physical Education, Liaoning Normal University, Dalian 116029, Liaoning, China.
College of Leisure and Social Sports, Capital University of Physical Education and Sports, Beijing, 100088 Beijing, China.
Comput Math Methods Med. 2022 Mar 7;2022:1991138. doi: 10.1155/2022/1991138. eCollection 2022.
With the continuous development of science and technology, people can apply more and more technology to the cultivation of children's abilities. In the process of cultivating children's ability, the most fancy is the study of executive function, and this is the research topic of this article. In the past, training methods such as music, mindfulness, and exercise have been used in the study of children's executive abilities to promote the development of preschool children's executive functions. While various approaches have had some effect, researchers have been exploring more comprehensive approaches to effective training. This article is aimed at studying how to use image recognition technology to conduct an intervention analysis of breakdancing in promoting the executive function of preschool children. For this reason, this paper proposes image recognition technology based on deep learning neural network and conducts research, analysis, and improvement on related technologies obtained from deep learning. This makes it more suitable for the research topic of this article and design-related experiments and analysis to explore its related performance. The experimental results in this paper show that the improved image recognition technology has improved accuracy by 31.2%. And the performance of its algorithm is also improved by 21%, which can be very effective in monitoring preschool children during breakdancing.
随着科学技术的不断发展,人们可以将越来越多的技术应用于培养儿童的能力。在培养儿童能力的过程中,最受关注的是执行功能的研究,这也是本文的研究课题。过去,在研究儿童执行能力的过程中,人们采用音乐、正念、运动等训练方法来促进学龄前儿童执行功能的发展。虽然各种方法都有一定的效果,但研究人员一直在探索更全面的有效训练方法。本文旨在研究如何利用图像识别技术对霹雳舞进行干预分析,以促进学龄前儿童的执行功能。为此,本文提出了基于深度学习神经网络的图像识别技术,并对从深度学习中获得的相关技术进行研究、分析和改进。这使得它更适合本文的研究课题和相关实验的设计与分析,以探索其相关性能。本文的实验结果表明,改进后的图像识别技术的准确率提高了 31.2%。并且其算法的性能也提高了 21%,这在监控学龄前儿童霹雳舞时非常有效。