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

机译:从科学网站数据的深度学习研究状态的生学计量分析

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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:通过从1968年到2018年从科学数据库Web获得的3599篇论文作为研究样本,本文展示了深度学习领域的研究状况,趋势和热点的全面的派对学习分析。结果表明,目前的全球深度学习研究具有很大的价值;大多数机构合作分别由中国和西方国家的大学和大学进行了不同的特征;深入学习领域的国际学术通信非常繁荣,集中在三大地区:东亚,北美和西欧。此外,目前的研究热点,如建模和算法研究,可以在关键词聚类映射中显示,目前的研究前线可以分为三层:计算机视觉技术,算法研究和建模的应用研究研究。

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