Deep Industrial Image Anomaly Detection: A Survey
文献类型：期刊论文
| 作者 | Jiaqi Liu4
|
| 刊名 | Machine Intelligence Research
 |
| 出版日期 | 2024 |
| 卷号 | 21期号:1页码:104-135 |
| ISSN号 | 2731-538X |
| 关键词 | Image anomaly detection, defect detection, industrial manufacturing, deep learning, computer vision |
| DOI | 10.1007/s11633-023-1459-z |
| 英文摘要 | The recent rapid development of deep learning has laid a milestone in industrial image anomaly detection (IAD). In this paper, we provide a comprehensive review of deep learning-based image anomaly detection techniques, from the perspectives of neural network architectures, levels of supervision, loss functions, metrics and datasets. In addition, we extract the promising setting from industrial manufacturing and review the current IAD approaches under our proposed setting. Moreover, we highlight several opening challenges for image anomaly detection. The merits and downsides of representative network architectures under varying supervision are discussed. Finally, we summarize the research findings and point out future research directions. More resources are available at https://github.com/M-3LAB/awesome-industrial-anomaly-detection. |
| 源URL | [http://ir.ia.ac.cn/handle/173211/54578]  |
| 专题 | 自动化研究所_学术期刊_International Journal of Automation and Computing |
| 作者单位 | 1.NICE Group, Bielefeld University, Bielefeld 33619, Germany 2.Youtu Lab, Tencent, Shanghai 200233, China 3.NICE Group, University of Surrey, Guildford GU2 7YX, UK 4.Research Institute of Trustworthy Autonomous Systems, Southern University of Science and Technology, Shenzhen 518055, China |
| 推荐引用方式 GB/T 7714 | Jiaqi Liu. Deep Industrial Image Anomaly Detection: A Survey[J]. Machine Intelligence Research,2024,21(1):104-135. |
| APA | Jiaqi Liu.(2024).Deep Industrial Image Anomaly Detection: A Survey.Machine Intelligence Research,21(1),104-135. |
| MLA | Jiaqi Liu."Deep Industrial Image Anomaly Detection: A Survey".Machine Intelligence Research 21.1(2024):104-135. |
入库方式： OAI收割
来源：自动化研究所
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