摘要
深度学习作为机器学习的一个分支,在图像处理,计算机视觉,自然语言等方面得到广泛的运用。而“运动科学”是以多学科融合交叉作为研究手段从而达到研究目的的学科,为使研究手段更加便利,研究结果更加精确,部分学者将深度学习的研究方法引入到运动科学的研究中,并取得了优异的成果。通过对现有的深度学习发展状况和在运动科学领域中的应用进行检索并综述,提出存在的问题和对未来的展望。综述表明,将深度学习运用到运动科学领域中时,使得运动科学的诸多问题开始倾向于工业化、信息化,简化了研究过程,提高了研究效率,深入了研究层次。但由于运动科学中计算机领域人才的缺失,使其泛化性不强。面对国际体育领域学术研究范式的根本性转变,需要运动科学的研究模式更应与其他学科进行融合交叉,将世界一流体育学科作为建设目标。
Deep learning, as a branch of machine learning, in image processing, computer vision, aspects, and so on natural language is widely used. And "Exercise Science" is a multidisciplinary fusion cross as a research method to study purpose, means to make research more convenient, more research results. This article through to the depth of the existing study development status and application in the field of “ExerciseScience” to retrieve and review, puts forward the problems and prospects for the future. Review shows that the application of deep learning in the field of Exercise Science makes many problems of Exercise Science begin to tend to industrialization, informationization, simplifies the research. But due to the lack of talents in the computer field in the sports science, make its generalization is not strong. The fundamental transition in the face of the international academic research paradigm in the field of sports, the need of Exercise Science research model should be a fusion cross with other disciplines, will be one of the worlds.
作者
梁思宇
井兰香
徐赟
LIANG Si-yu;Jing Lan-xiang;XU Yun(Physical Education College of Yanshan University,Qinhuangdao 066000,China;Polytechnic Institute,Zhejiang University,Hangzhou 310058,China)
出处
《浙江体育科学》
2023年第2期98-105,共8页
Zhejiang Sport Science
基金
河北省社会发展研究课题(20220202458)。
关键词
人工智能
深度学习
运动科学
运动想象-脑机接口
关键点检测
Artificial Intelligence
Deep Learning
Exercise Science
Motor Imagery-Brain Computer Interface
The key test
