A Review on Research and Application of AI-Based Image Analysis in the Field of Computer Vision

IF 3.4 3区计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

IEEE Access Pub Date : 2025-04-29 DOI:10.1109/ACCESS.2025.3565300

Pan Wu;Xiaoqiang He;Wenhao Dai;Jingwei Zhou;Yutong Shang;Yourong Fan;Tao Hu

{"title":"A Review on Research and Application of AI-Based Image Analysis in the Field of Computer Vision","authors":"Pan Wu;Xiaoqiang He;Wenhao Dai;Jingwei Zhou;Yutong Shang;Yourong Fan;Tao Hu","doi":"10.1109/ACCESS.2025.3565300","DOIUrl":null,"url":null,"abstract":"The rapid development of artificial intelligence has significantly advanced the field of computer vision, particularly in image analysis and understanding. This paper provides a comprehensive review of the current state of the field, key technologies, and their applications across various real-world scenarios. It delves into the value of image analysis in critical areas such as personalized art, healthcare and medical image analysis, security monitoring and recognition technology, autonomous driving and traffic management, as well as industrial automation and quality control. This paper not only highlights the challenges and limitations, including dataset constraints, algorithm generalization, real-time computational costs, and privacy and ethical concerns, but also offers a forward-looking analysis of development trends such as interdisciplinary integration, weakly supervised and unsupervised learning, algorithm optimization and hardware advancements, and the protection of personal privacy and information. These insights provide a profound perspective on the future trajectory of computer vision and AI-driven image analysis.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"76684-76702"},"PeriodicalIF":3.4000,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10979847","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Access","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10979847/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}

引用次数: 0

Abstract

The rapid development of artificial intelligence has significantly advanced the field of computer vision, particularly in image analysis and understanding. This paper provides a comprehensive review of the current state of the field, key technologies, and their applications across various real-world scenarios. It delves into the value of image analysis in critical areas such as personalized art, healthcare and medical image analysis, security monitoring and recognition technology, autonomous driving and traffic management, as well as industrial automation and quality control. This paper not only highlights the challenges and limitations, including dataset constraints, algorithm generalization, real-time computational costs, and privacy and ethical concerns, but also offers a forward-looking analysis of development trends such as interdisciplinary integration, weakly supervised and unsupervised learning, algorithm optimization and hardware advancements, and the protection of personal privacy and information. These insights provide a profound perspective on the future trajectory of computer vision and AI-driven image analysis.

查看原文本刊更多论文

基于人工智能的图像分析在计算机视觉领域的研究与应用综述

人工智能的快速发展极大地推动了计算机视觉领域的发展，特别是在图像分析和理解方面。本文全面回顾了该领域的现状、关键技术及其在各种现实场景中的应用。它深入探讨了图像分析在关键领域的价值，如个性化艺术，医疗保健和医学图像分析，安全监控和识别技术，自动驾驶和交通管理，以及工业自动化和质量控制。本文不仅强调了挑战和局限性，包括数据集约束、算法泛化、实时计算成本、隐私和伦理问题，而且对跨学科融合、弱监督和无监督学习、算法优化和硬件进步、个人隐私和信息保护等发展趋势进行了前瞻性分析。这些见解为计算机视觉和人工智能驱动的图像分析的未来轨迹提供了深刻的视角。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

IEEE Access COMPUTER SCIENCE, INFORMATION SYSTEMSENGIN-ENGINEERING, ELECTRICAL & ELECTRONIC

CiteScore

9.80

自引率

7.70%

发文量

6673

审稿时长

6 weeks

期刊介绍： IEEE Access® is a multidisciplinary, open access (OA), applications-oriented, all-electronic archival journal that continuously presents the results of original research or development across all of IEEE''s fields of interest. IEEE Access will publish articles that are of high interest to readers, original, technically correct, and clearly presented. Supported by author publication charges (APC), its hallmarks are a rapid peer review and publication process with open access to all readers. Unlike IEEE''s traditional Transactions or Journals, reviews are "binary", in that reviewers will either Accept or Reject an article in the form it is submitted in order to achieve rapid turnaround. Especially encouraged are submissions on: Multidisciplinary topics, or applications-oriented articles and negative results that do not fit within the scope of IEEE''s traditional journals. Practical articles discussing new experiments or measurement techniques, interesting solutions to engineering. Development of new or improved fabrication or manufacturing techniques. Reviews or survey articles of new or evolving fields oriented to assist others in understanding the new area.