国内基于深度学习的目标跟踪研究知识图谱分析

Analysis of Knowledge Map of Domestic Research on Target Tracking Based on Deep Learning by CiteSpace

【目的/意义】基于深度学习的目标跟踪研究在国内研究热潮的迅速高涨,吸引了多位来自计算机视觉领域学者产出丰硕的成果,知识图谱能直观地揭示该领域的研究概况与前沿。【方法/过程】利用CiteSpace分析软件,以中国知网引文索引(CNKI)数据库为数据源,搜集基于深度学习的目标跟踪研究相关文献数据。从时空分布、机构与作者分布、关键词频度共现、研究趋势变化时序图谱等方面,绘制知识图谱,梳理研究脉络,揭示国内基于深度学习对目标跟踪的研究现状与发展方向。【结果/结论】以客观数据和图谱为依据,对基于深度学习对目标跟踪的研究发展进行分析和总结,同时提出相关建议,为该领域的后续研究提供参考。

【Purpose/significance】The rapid upsurge of research on target tracking based on deep learning in China has attracted many scholars from the field of computer vision to produce fruitful results. Knowledge map can intuitively reveal the research overview and frontier of this field.【Method/process】Taking the Chinese CNKI citation index database as the data source, the related literature datas of target tracking based on deep learning are collected by using CiteSpace,the knowledge map is drawed by combing the research context from the following aspects: the temporal and spatial distribution, cooperation and author field, Keyword frequency co-occurrence, time sequence map of trend change research, which reveals the research status and development direction of domestic target tracking based on deep learning.【Result/conclusion】Based on the objective data and map, the research and development of target tracking based on deep learning are analyzed and summarized, and relevant suggestions are put forward, which provide reference for the follow-up study in this field.