Yanliang Pei

Dr. Yanliang Pei


Research Focus & Metrics

Academic Career Length

18Years (2009-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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Verified
Journal Article
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NYNa Yang
Na Yang
GLGuoyu Li
Guoyu Li
SWShengli Wang
Shengli Wang
ZWZhengrong Wei
Zhengrong Wei
HRHu Ren
Hu Ren
YPYanliang Pei
Yanliang Pei
As seabed exploration activities increase, side-scan sonar (SSS) is being used more widely. However, distortion and noise during the acoustic pulse’s travel through water can blur target details and cause feature loss in images, making target recognition more challenging. In this paper, we improve the YOLO model in two aspects: lightweight design and accuracy enhancement. The lightweight design is essential for reducing computational complexity and resource consumption, allowing the model to be more efficient on edge devices with limited processing power and storage. Thus, meeting our need to deploy SSS target detection algorithms on unmanned surface vessel (USV) for real-time target detection. Firstly, we replace the original complex convolutional method in the C2f module with a combination of partial convolution (PConv) and pointwise convolution (PWConv), reducing redundant computations and memory access while maintaining high accuracy. In addition, we add an adaptive scale spatial fusion (ASSF) module using 3D convolution to combine feature maps of different sizes, maximizing the extraction of invariant features across various scales. Finally, we use an improved multi-head self-attention (MHSA) mechanism in the detection head, replacing the original complex convolution structure, to enhance the model’s ability to focus on important features with low computational load. To validate the detection performance of the model, we conducted experiments on the combined side-scan sonar dataset (SSSD). The results show that our proposed SS-YOLO model achieves average accuracies of 92.4% (mAP 0.5) and 64.7% (mAP 0.5:0.95), outperforming the original YOLOv8 model by 4.4% and 3%, respectively. In terms of model complexity, the improved SS-YOLO model has 2.55 M of parameters and 6.4 G of FLOPs, significantly lower than those of the original YOLOv8 model and similar detection models.

13 January 2017 in International Journal of Remote Sensing
Verified
Journal Article
Closed access
YPYanliang Pei
Yanliang Pei
BLBaohua Liu
Baohua Liu
QHQingfeng Hua
Qingfeng Hua
CLChenguang Liu
Chenguang Liu
YJYuqiang Ji
Yuqiang Ji
China has very long coastline, but special surface conditions make it very difficult to conduct ground magnetic and marine geomagnetic surveys over beach–shallow sea transition areas such as mariculture areas, harbours, and wharfs; as a result, marine survey data cannot be linked to continental survey data, giving rise to missing data. To address this issue, an aeromagnetic survey technology based on an unmanned autonomous helicopter is proposed. Not only is an unmanned autonomous helicopter capable of aeromagnetic surveying the beach–shallow sea transition area inaccessible to vehicles and vessels but its high efficiency and low cost also enable it to be deployed on a vessel, thus making it suitable for aeromagnetic surveying oceanic islands, too. The setup of the aeromagnetic survey system based on an unmanned aerial vehicle (UAV) is introduced, and its trial flight information and processed and analysed magnetic survey data obtained in trial flights are discussed. The measurement accuracy of UAV aeromagnetic data is shown to be comparable to that of marine geomagnetic survey data, and the system effectively compensates for missing magnetic data from inshore and continent–ocean transition zones.

13 June 2010 in Chinese Science Bulletin
Verified
Journal Article
Closed access
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XLXishuang Li
Xishuang Li
YZYueXia Zhao
YueXia Zhao
BLBaoHua Liu
BaoHua Liu
CLChenGuang Liu
ChenGuang Liu
YPYanliang Pei
Yanliang Pei
QHQingfeng Hua
Qingfeng Hua

1 November 2019 in Journal of Applied Geophysics
Verified
Journal Article
Closed access
YPYanliang Pei
Yanliang Pei
GKGuangming Kan
Guangming Kan
LZLiancheng Zhang
Liancheng Zhang
YHYifan Huang
Yifan Huang
ZLZhen Liu
Zhen Liu
KYKeping Yan
Keping Yan

19 July 2016 in Acta Oceanologica Sinica
Verified
Journal Article
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JZJiewen Zheng
Jiewen Zheng
BLBaohua Liu
Baohua Liu
GKGuangming Kan
Guangming Kan
GLGuanbao Li
Guanbao Li
YPYanliang Pei
Yanliang Pei
Xiaolei LiuXiaolei Liu
Xiaolei Liu

26 July 2017 in Plasma Science and Technology
Verified
Journal Article
Closed access
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YPYanliang Pei
Yanliang Pei
LZLiancheng Zhang
Liancheng Zhang
YHYifan Huang
Yifan Huang
HYHui Yan
Hui Yan
XZXinlei Zhu
Xinlei Zhu
KYKeping Yan
Keping Yan
A multi-electrode array is commonly applied in a plasma sparker to generate stable acoustic pulses. In this paper, the effects of the electrode configuration on the performance of a plasma sparker have been investigated. In terms of the load electrical characteristics, the electrode radius and distance have negligible influence on the electric characteristics, whereas a larger electrode number results in a smaller voltage and a larger current but has little effect on the load energy. Regarding the acoustic characteristics, both the expansion and collapse pulses can be increased by decreasing the electrode tip radius. the influence of the electrode number and electrode gap distance on the amplitude of the expansion pulse was found to be negligible. And the amplitude of the collapse pulse decreases significantly with increasing electrode number. Increasing the electrode number decreases the energy efficiency for intense bubble interactions, thus, a small electrode tip radius and a small electrode number are preferred for the design of a plasma sparker if the total discharge energy is given.