TCM Model for improving track sequence classification in real scenarios with Multi-Feature Fusion and Transformer Block
文献类型：期刊论文
| 作者 | Xiang, Ti1,2; Lv, Pin2 ; Sun, Liguo2; Yang, Yipu2,3; Hao, Jiuwu1,2
|
| 刊名 | KNOWLEDGE-BASED SYSTEMS
 |
| 出版日期 | 2024-01-11 |
| 卷号 | 283页码:13 |
| 关键词 | Track classification Multi-feature fusion Marine radar Transformer |
| ISSN号 | 0950-7051 |
| DOI | 10.1016/j.knosys.2023.111202 |
| 通讯作者 | Lv, Pin() |
| 英文摘要 | The shipping industry has experienced rapid growth in recent years, prompting a need for advanced target recognition technology based on marine radar. This paper introduces the Track Classification Model (TCM), a novel approach for classifying track sequences in real scenarios. The TCM utilizes a feature extraction network based on multi-feature fusion, taking radar echo images and motion information of the target as input, to improve classification accuracy. Additionally, the paper also presents a dataset production method that addresses the issue of missing labels, a critical problem in track sequence classification. Through ablation experiments, the paper demonstrates the effectiveness of the design strategy, with the multi-feature fusion network successfully extracting features and achieving superior performance over single feature extraction networks. The results show that increasing the number of input track points and raising the upper limit of the input sequence leads to improved classification accuracy. Finally, in real scenarios, the proposed model outperforms other algorithms, showcasing its high engineering application value. |
| 资助项目 | National Key Research and Development Program of China[2022ZD0116409] |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:001124036300001 |
| 出版者 | ELSEVIER |
| 资助机构 | National Key Research and Development Program of China |
| 源URL | [http://ir.ia.ac.cn/handle/173211/55024]  |
| 专题 | 复杂系统认知与决策实验室 |
| 通讯作者 | Lv, Pin |
| 作者单位 | 1.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 300400, Peoples R China 2.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 3.Hebei Univ Technol, Sch Elect & Informat Engn, Tianjin 300400, Peoples R China |
| 推荐引用方式 GB/T 7714 | Xiang, Ti,Lv, Pin,Sun, Liguo,et al. TCM Model for improving track sequence classification in real scenarios with Multi-Feature Fusion and Transformer Block[J]. KNOWLEDGE-BASED SYSTEMS,2024,283:13. |
| APA | Xiang, Ti,Lv, Pin,Sun, Liguo,Yang, Yipu,&Hao, Jiuwu.(2024).TCM Model for improving track sequence classification in real scenarios with Multi-Feature Fusion and Transformer Block.KNOWLEDGE-BASED SYSTEMS,283,13. |
| MLA | Xiang, Ti,et al."TCM Model for improving track sequence classification in real scenarios with Multi-Feature Fusion and Transformer Block".KNOWLEDGE-BASED SYSTEMS 283(2024):13. |
入库方式： OAI收割
来源：自动化研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。