Deep learning architecture for anomaly detection, classification, and localization in free-space optical communication

SONG Song; WU Tingwei; ZHAO Lun; JIA Jiaqing; GUO Lei

doi:10.11959/j.issn.1000-436x.2025197

您当前的位置：

首页 >

文章列表页 >

Deep learning architecture for anomaly detection, classification, and localization in free-space optical communication

Topics: Theoretical Technology of Free-Space Optical (FSO) Communications | 更新时间：2025-11-25

- Deep learning architecture for anomaly detection, classification, and localization in free-space optical communication
- Journal on Communications Vol. 46, Issue 10, Pages: 1-14(2025)
- 作者机构：
  
  1.重庆邮电大学通信与信息工程学院，重庆 400065
  2.重庆邮电大学智能通信与网络安全研究院学院，重庆 400065
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(62401092;62301097;62025105;U24A20216);The China Postdoctoral Science Foundation(2024M763913);The Chongqing Municipal Science and Technology Bureau(CSTB2024NSCQ-MSX0991);The Chongqing Municipal Education Commission(KJQN202400630);The Chongqing human resources and Social Security Bureau(2024CQBSHTB3072);The Exchange Project for Key Lab of Optical Fiber Sensing and Communications (Ministry of Education of China)(ZYGX2024K010)
- DOI：10.11959/j.issn.1000-436x.2025197
  CLC： TN929.1
- Received：07 August 2025，
  
  Revised：2025-10-30，
  
  Accepted：31 October 2025，
  
  Published：20 October 2025
- 稿件说明：
移动端阅览
宋嵩,吴廷伟,赵伦等.自由空间光通信的异常检测、分类与定位深度学习架构[J].通信学报,2025,46(10):1-14.

SONG Song,WU Tingwei,ZHAO Lun,et al.Deep learning architecture for anomaly detection, classification, and localization in free-space optical communication[J].Journal on Communications,2025,46(10):1-14.
宋嵩,吴廷伟,赵伦等.自由空间光通信的异常检测、分类与定位深度学习架构[J].通信学报,2025,46(10):1-14. DOI： 10.11959/j.issn.1000-436x.2025197.

SONG Song,WU Tingwei,ZHAO Lun,et al.Deep learning architecture for anomaly detection, classification, and localization in free-space optical communication[J].Journal on Communications,2025,46(10):1-14. DOI： 10.11959/j.issn.1000-436x.2025197.

Views

1002

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Review of unsupervised anomaly detection techniques for medical imaging

Target visibility prediction method based on cost-sensitive CNN-BiLSTM network

Multi-modal semantics aided mmWave beam prediction method in industrial haze environment

Related Author

Zhao Yingcheng

Song Xiaogang

Shi Zhenghao

You Zhenzhen

Hei Xinhong

Liao Xi

Lin Ruijia

Zheng Xiangquan

Related Institution

School of Computer Science and Engineering, Xi’an University of Technology

Shaanxi Key Laboratory for Network Computing and Security Technology

Human Machine Integration Intelligent Robot Shaanxi Provincial University Engineering Research Center

School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications

PLA Unit

AI导读

AI脑图

AI问答

⁰

Deep learning architecture for anomaly detection, classification, and localization in free-space optical communication

DOI：10.11959/j.issn.1000-436x.2025197