Bibliometric Analysis of the Application of Convolutional Neural Network in Computer Vision
Chen Huie, Zhenjie Deng
Abstract
This article analyzes the research progress in field of Convolutional Neural Networks (CNNs) using the bibliometric method. Literature samples of CNNs are analyzed by a basic statistic and co-citation network. Experimental results show that CNNs are being utilized in many computer vision applications, such as fault and image recognition diagnosis, seismic detection, positioning, and automatic detection of cracks and signals, image classification and image segmentation. In addition, there is systematic research on unbalanced problems in CNNs. Quantitative experimental research, extensive application fields, and market research informatization will be the three vital research tendencies in the future. The ideas and conclusions of this article provide insights to the academic research of CNNs and their practical application in the corporate world.