首页> 外文会议>International conference on swarm intelligence;International conderence on data mining and big data >Bibliometric Analysis of the Deep Learning Research Status with the Data from Web of Science
【24h】

Bibliometric Analysis of the Deep Learning Research Status with the Data from Web of Science

机译:Web of Science数据对深度学习研究现状的文献计量分析

获取原文

摘要

By using the 3599 papers obtained from the Web of Science database from 1968 to 2018 as the research sample, this paper demonstrates a comprehensive Bibliometric analysis of the research status, trends and hotspots in the domain of Deep Learning. The results indicate that the current global deep learning research is of great value; most of the institution cooperation are conducted with different characteristics by colleges and universities in China and Western Countries, respectively; the international academic communications in the deep learning field are pretty prosperous, which are concentrated on three major region: East Asia, North America, and West Europe. In addition, the current research hotspots, such as modeling and algorithm research can be shown in a keywords clustering mapping, and the current research fronts can be categorized into three layers: the application research of computer vision technology, the algorithm research, and the modeling research.
机译:通过使用1968年至2018年从Web of Science数据库获得的3599篇论文作为研究样本,该论文展示了深度学习领域研究现状,趋势和热点的综合文献计量分析。结果表明,当前的全球深度学习研究具有重要的价值。多数机构合作是由中国和西方国家的大学分别进行的,具有不同的特点。深度学习领域的国际学术交流非常繁荣,主要集中在三个主要地区:东亚,北美和西欧。另外,当前的研究热点,例如建模和算法研究,可以在关键词聚类映射中显示出来,当前的研究前沿可以分为三层:计算机视觉技术的应用研究,算法研究和建模。研究。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号