The following publications are possibly variants of this publication:
- A Novel Target Detection Method of the Unmanned Surface Vehicle under All-Weather Conditions with an Improved YOLOV3Yan Li, Jiahong Guo, Xiaomin Guo, Kaizhou Liu, Wentao Zhao, Yeteng Luo, Zhenyu Wang. sensors, 20(17):4885, 2020. [doi]
- Mlvit-YoloX: a lightweight maritime surface object detector based transformer for unmanned surface vehiclesLonghui Niu, Yunsheng Fan, Ting Liu, Qi Han. cluster, 28(9):583, October 2025. [doi]
- Challenge-based collaborative intrusion detection networks under passive message fingerprint attack: A further analysisWenjuan Li, Lam-for Kwok. istr, 47:1-7, 2019. [doi]
- Research on Target Detection Algorithm of Unmanned Surface Vehicle Based on Deep LearningFan Huang, Yong Chen, Xinlong Pan, Haipeng Wang, Heng Fang. bic-ta 2023: 275-289 [doi]
- Vehicle Multi-target Detection in Foggy Scene Based on Foggy env-YOLO AlgorithmXiyun Wang, Chao Wang. icite 2022: 451-456 [doi]
- Unmanned Surface Vessel Visual Object Detection Under All-Weather Conditions with Optimized Feature Fusion Network in YOLOv4Xiaoqiang Sun, Tao Liu, Xiuping Yu, Bo Pang. jirs, 103(3):55, 2021. [doi]
- A Novel Dense Generative Net Based on Satellite Remote Sensing Images for Vehicle Classification Under Foggy Weather ConditionsJianjun Yuan, Tong Liu, Haobo Xia, Xu Zou. tgrs, 61:1-10, 2023. [doi]