A bibliometric review of technical applications of deep learning in computer vision

Abstract

Computer vision is a field of Artificial Intelligence (AI), which is the field of technology that allows computers and systems to capture meaningful information from visual inputs such as images, videos, etc. through external cameras, data, and internal algorithms, and to take action or provide recommendations based on the captured information. Common application scenarios of computer vision are image recognition, image classification, object detection, pose detection, image segmentation, etc. In the era of artificial intelligence, computer vision plays the role of a "perceptron", which is the "eye" of the artificial intelligence era, and provides the "planning" and "decision-making" for the artificial intelligence. "Decision-making" provides an effective source of information and information support, and promotes the breakthrough development of computer vision technology while realising the iterative update of AI technology. By 2022, the market value of this field reaches $48.6 billion. In this paper, a visual knowledge graph data analysis of relevant literature on Web of Science (WOS) and China National Knowledge Infrastructure(CNKI) was conducted through CiteSpace. Among them, it focuses on analysing the development trend of image restoration technology based on diffusion model, which provides some help for scholars to carry out research.