A Restricted Embedding Transfer Model for Hyperspectral Anomaly Detection
文献类型：会议论文
| 作者 | Shi, Chenliang2; Qiu, Shi1
|
| 出版日期 | 2023 |
| 会议日期 | 2023-08-25 |
| 会议地点 | Hybrid, Nanjing, China |
| 关键词 | image processing anomaly detection hyperspectral image deep learning transfer learning semi supervised learning |
| DOI | 10.1109/ICBASE59196.2023.10303063 |
| 页码 | 340-348 |
| 英文摘要 | The purpose of hyperspectral image anomaly detection is to overcome the problem of inconsistent background distribution, suppress background information as much as possible, and highlight anomalous target information. Many existing deep learning anomaly detection methods use generative algorithms, such as those based on generative adversarial networks and those based on automatic encoders, but these algorithms are inevitably accompanied by the problem of low reconstruction accuracy or poor calibration. In order to solve these problems, this paper proposes a restricted embedding transfer model for hyperspectral image anomaly detection, which transforms the anomaly detection problem into a feature regression problem through partial knowledge transfer learning. Thus it avoiding the need for reconstruction or probability distribution evaluation. The teacher network adaptively generates descriptive embedding vectors that are used as pseudo-labels to assist the training of the student network, and only part of the normal sample is needed to complete the training. In the experimental part, the performance of the proposed method is compared with seven existing methods on twelve hyperspectral datasets. The results show that the proposed method has better detection effect, and the AUC index reaches 0.9789, which is 0.0109 higher than the second place. © 2023 IEEE. |
| 产权排序 | 2 |
| 会议录 | 2023 4th International Conference on Big Data and Artificial Intelligence and Software Engineering, ICBASE 2023
 |
| 会议录出版者 | Institute of Electrical and Electronics Engineers Inc. |
| 语种 | 英语 |
| ISBN号 | 9798350329490 |
| 源URL | [http://ir.opt.ac.cn/handle/181661/97046]  |
| 专题 | 西安光学精密机械研究所_光学影像学习与分析中心 |
| 作者单位 | 1.Xi'an Institute of Optics & Precision Mechanics, Chinese Academy of Sciences, Xi'an, China 2.Shaanxi Normal University, Chinese Academy of Sciences, Xi'an Institute of Optics & Precision Mechanics, Xi'an, China; |
| 推荐引用方式 GB/T 7714 | Shi, Chenliang,Qiu, Shi. A Restricted Embedding Transfer Model for Hyperspectral Anomaly Detection[C]. 见:. Hybrid, Nanjing, China. 2023-08-25. |
入库方式： OAI收割
来源：西安光学精密机械研究所
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