Pei An

1.3k total citations · 1 hit paper
38 papers, 767 citations indexed

About

Pei An is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Geology. According to data from OpenAlex, Pei An has authored 38 papers receiving a total of 767 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Computer Vision and Pattern Recognition, 22 papers in Aerospace Engineering and 7 papers in Geology. Recurrent topics in Pei An's work include Robotics and Sensor-Based Localization (19 papers), Advanced Vision and Imaging (10 papers) and Optical measurement and interference techniques (8 papers). Pei An is often cited by papers focused on Robotics and Sensor-Based Localization (19 papers), Advanced Vision and Imaging (10 papers) and Optical measurement and interference techniques (8 papers). Pei An collaborates with scholars based in China, United Kingdom and Iraq. Pei An's co-authors include Yanfei Chen, Gang Wang, Tiange Huang, Hanyu Hong, Jie Ma, Bin Fang, Kun Yu, Qiong Liu, You Yang and Jun Zhang and has published in prestigious journals such as Optics Express, IEEE Access and Sensors.

In The Last Decade

Pei An

34 papers receiving 738 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

UAV-YOLOv8: A Small-Object-Detection Model Based on Improved YOLOv8 for UAV Aerial Photography Scenarios

2023 447 citations Gang Wang, Yanfei Chen et al. Sensors profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Pei An China	11	396	275	83	71	66	38	767
Xinyue Zhao China	17	503 1.3×	173 0.6×	140 1.7×	112 1.6×	63 1.0×	70	785
Zhuofan Xia China	5	605 1.5×	214 0.8×	88 1.1×	18 0.3×	129 2.0×	10	946
Jacek Naruniec Poland	7	550 1.4×	168 0.6×	88 1.1×	28 0.4×	77 1.2×	19	748
Junbo Yin China	13	729 1.8×	304 1.1×	67 0.8×	33 0.5×	69 1.0×	26	965
Zhaozheng Hu China	14	273 0.7×	206 0.7×	34 0.4×	66 0.9×	59 0.9×	63	687
Jin Fang China	12	721 1.8×	367 1.3×	84 1.0×	25 0.4×	77 1.2×	22	1.0k
Cihan Topal Türkiye	12	737 1.9×	346 1.3×	62 0.7×	49 0.7×	146 2.2×	47	963
Zhiying Tan China	13	255 0.6×	244 0.9×	48 0.6×	70 1.0×	31 0.5×	62	656
Massimiliano Nitti Italy	17	476 1.2×	116 0.4×	170 2.0×	177 2.5×	75 1.1×	63	842

Countries citing papers authored by Pei An

Since Specialization

Citations

This map shows the geographic impact of Pei An's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Pei An with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pei An more than expected).

Fields of papers citing papers by Pei An

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pei An. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Pei An. The network helps show where Pei An may publish in the future.

Co-authorship network of co-authors of Pei An

This figure shows the co-authorship network connecting the top 25 collaborators of Pei An. A scholar is included among the top collaborators of Pei An based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Pei An. Pei An is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

An, Pei, et al.. (2025). FSF-Net: Enhance 4D occupancy forecasting with coarse BEV scene flow for autonomous driving. Pattern Recognition. 172. 112372–112372. 1 indexed citations

2.

Dang, Chuangyin, et al.. (2025). SDGOCC: Semantic and Depth-Guided Bird’s-Eye View Transformation for 3D Multimodal Occupancy Prediction. 6751–6760. 1 indexed citations

3.

Zeng, Zhi, Xiyu Zhang, Lin Wu, et al.. (2025). Unlocking Generalization Power in LiDAR Point Cloud Registration. 22244–22253.

4.

An, Pei, et al.. (2024). Vision-Based Drone Detection in Complex Environments: A Survey. Drones. 8(11). 643–643. 13 indexed citations

5.

An, Pei, Di Zhu, Siwen Quan, et al.. (2024). ESC-Net: Alleviating Triple Sparsity on 3D LiDAR Point Clouds for Extreme Sparse Scene Completion. IEEE Transactions on Multimedia. 26. 6799–6810. 5 indexed citations

6.

An, Pei, Siwen Quan, Jiaqi Yang, et al.. (2024). Survey of Extrinsic Calibration on LiDAR-Camera System for Intelligent Vehicle: Challenges, Approaches, and Trends. IEEE Transactions on Intelligent Transportation Systems. 25(11). 15342–15366. 4 indexed citations

7.

An, Pei, Jianfu Ding, Jun Zhang, et al.. (2024). OL-Reg: Registration of Image and Sparse LiDAR Point Cloud With Object-Level Dense Correspondences. IEEE Transactions on Circuits and Systems for Video Technology. 34(8). 7523–7536. 4 indexed citations

8.

An, Pei, Yucong Duan, Jie Ma, et al.. (2023). SP-Det: Leveraging Saliency Prediction for Voxel-Based 3D Object Detection in Sparse Point Cloud. IEEE Transactions on Multimedia. 26. 2795–2808. 16 indexed citations

9.

An, Pei, Jie Ma, Yanfei Chen, et al.. (2023). RS-Aug: Improve 3D Object Detection on LiDAR With Realistic Simulator Based Data Augmentation. IEEE Transactions on Intelligent Transportation Systems. 24(9). 10165–10176. 7 indexed citations

10.

An, Pei, et al.. (2023). Leveraging Self-Paced Semi-Supervised Learning with Prior Knowledge for 3D Object Detection on a LiDAR-Camera System. Remote Sensing. 15(3). 627–627. 4 indexed citations

11.

Wang, Gang, et al.. (2023). UAV-YOLOv8: A Small-Object-Detection Model Based on Improved YOLOv8 for UAV Aerial Photography Scenarios. Sensors. 23(16). 7190–7190. 447 indexed citations breakdown →

12.

Zhang, Jun, et al.. (2023). Novel Geometric Calibration Method for Pan-Tilt Camera With Single Control Point. IEEE Access. 11. 34175–34185.

13.

Ma, Tao, et al.. (2023). Stereo Image Dense Matching Based on SGM Constrained by Feature Matching. 1911–1915.

14.

An, Pei, et al.. (2023). A Robust LiDAR-Camera Self-Calibration Via Rotation-Based Alignment and Multi-Level Cost Volume. IEEE Robotics and Automation Letters. 9(1). 627–634. 4 indexed citations

15.

An, Pei, Wenxing Fu, Jie Ma, et al.. (2021). Lambertian Model-Based Normal Guided Depth Completion for LiDAR-Camera System. IEEE Geoscience and Remote Sensing Letters. 19. 1–5. 6 indexed citations

16.

Yu, Kun, et al.. (2021). NCFT: Automatic Matching of Multimodal Image Based on Nonlinear Consistent Feature Transform. IEEE Geoscience and Remote Sensing Letters. 19. 1–5. 9 indexed citations

17.

An, Pei, et al.. (2018). Vision-Based Simultaneous Localization and Mapping on Lunar Rover. 487–493. 5 indexed citations

18.

An, Pei, et al.. (2017). A survey of simultaneous localization and mapping on unstructured lunar complex environment. AIP conference proceedings. 1890. 30010–30010. 10 indexed citations

19.

An, Pei. (1998). PC interfacing : using Centronic, RS232 and game ports. 3 indexed citations

20.

He, S., et al.. (1998). Combined heat and mass transfer in a uniformly heated vertical tube with water film cooling. International Journal of Heat and Fluid Flow. 19(5). 401–417. 26 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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