Pengcheng Shi

1.2k total citations
54 papers, 516 citations indexed

About

Pengcheng Shi is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Biomedical Engineering. According to data from OpenAlex, Pengcheng Shi has authored 54 papers receiving a total of 516 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Computer Vision and Pattern Recognition, 12 papers in Aerospace Engineering and 11 papers in Biomedical Engineering. Recurrent topics in Pengcheng Shi's work include Medical Image Segmentation Techniques (21 papers), Robotics and Sensor-Based Localization (12 papers) and Elasticity and Material Modeling (9 papers). Pengcheng Shi is often cited by papers focused on Medical Image Segmentation Techniques (21 papers), Robotics and Sensor-Based Localization (12 papers) and Elasticity and Material Modeling (9 papers). Pengcheng Shi collaborates with scholars based in China, Hong Kong and United States. Pengcheng Shi's co-authors include Jiayuan Li, Yongjun Zhang, Qingwu Hu, Huafeng Liu, James S. Duncan, Albert J. Sinusas, R. Todd Constable, Huafeng Liu, Qin Ye and Anne R. Haake and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, NeuroImage and IEEE Transactions on Geoscience and Remote Sensing.

In The Last Decade

Pengcheng Shi

50 papers receiving 495 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pengcheng Shi China 13 292 146 103 90 59 54 516
Anna Hilsmann Germany 14 285 1.0× 55 0.4× 144 1.4× 174 1.9× 21 0.4× 93 632
Joakim Rydell Sweden 12 128 0.4× 164 1.1× 92 0.9× 53 0.6× 34 0.6× 47 571
Pengxiang Wu United States 14 516 1.8× 121 0.8× 150 1.5× 70 0.8× 27 0.5× 25 832
Simon Prince United Kingdom 13 198 0.7× 199 1.4× 129 1.3× 135 1.5× 34 0.6× 61 594
Diego Santa-Cruz Switzerland 7 584 2.0× 38 0.3× 50 0.5× 63 0.7× 28 0.5× 11 828
Sébastien Valette France 12 294 1.0× 36 0.2× 42 0.4× 59 0.7× 18 0.3× 41 633
Daniel Kondermann Germany 11 370 1.3× 83 0.6× 128 1.2× 49 0.5× 24 0.4× 24 574
J.J. Villanueva Spain 9 340 1.2× 31 0.2× 68 0.7× 26 0.3× 21 0.4× 33 451
Arun Das United States 11 167 0.6× 165 1.1× 40 0.4× 18 0.2× 64 1.1× 31 369
Paulo Gotardo United States 15 660 2.3× 210 1.4× 28 0.3× 30 0.3× 23 0.4× 38 760

Countries citing papers authored by Pengcheng Shi

Since Specialization
Citations

This map shows the geographic impact of Pengcheng Shi'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 Pengcheng Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pengcheng Shi more than expected).

Fields of papers citing papers by Pengcheng Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pengcheng Shi. 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 Pengcheng Shi. The network helps show where Pengcheng Shi may publish in the future.

Co-authorship network of co-authors of Pengcheng Shi

This figure shows the co-authorship network connecting the top 25 collaborators of Pengcheng Shi. A scholar is included among the top collaborators of Pengcheng Shi 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 Pengcheng Shi. Pengcheng Shi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Shi, Pengcheng, et al.. (2025). Indoor scan-to-BIM automation: From mobile perception to 3D building modelling. Automation in Construction. 182. 106731–106731.
2.
Yin, Qianlan, Jing Wen, Shuo Chen, et al.. (2025). Uncovering the neural basis of risk preferences in cooperative Dyads: A fNIRS study. NeuroImage. 310. 121167–121167. 1 indexed citations
3.
Ding, Xiaojian, et al.. (2024). Multi-view Stable Feature Selection with Adaptive Optimization of View Weights. Knowledge-Based Systems. 299. 111970–111970. 2 indexed citations
4.
Zhang, Yongjun, Pengcheng Shi, & Jiayuan Li. (2024). LiDAR-Based Place Recognition For Autonomous Driving: A Survey. ACM Computing Surveys. 57(4). 1–36. 14 indexed citations
5.
Wang, Hui, Xiangyang Li, Pengcheng Shi, Xiaoyan You, & Guoping Zhao. (2024). Establishment and evaluation of on-chip intestinal barrier biosystems based on microfluidic techniques. Materials Today Bio. 26. 101079–101079. 14 indexed citations
6.
Shi, Pengcheng, et al.. (2024). A New Horizon: Employing Map Clustering Similarity for LiDAR-Based Place Recognition. IEEE Transactions on Intelligent Vehicles. 9(10). 5995–6005. 4 indexed citations
7.
Li, Jiayuan, Pengcheng Shi, Qingwu Hu, & Yongjun Zhang. (2023). QGORE: Quadratic-Time Guaranteed Outlier Removal for Point Cloud Registration. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(9). 11136–11151. 27 indexed citations
8.
Shi, Pengcheng, Jiayuan Li, & Yongjun Zhang. (2023). LiDAR localization at 100 FPS: A map-aided and template descriptor-based global method. International Journal of Applied Earth Observation and Geoinformation. 120. 103336–103336. 9 indexed citations
9.
Yu, Qi, et al.. (2020). Dynamic Fusion of Eye Movement Data and Verbal Narrations in Knowledge-rich Domains. Neural Information Processing Systems. 33. 2062–2073. 1 indexed citations
10.
Pelz, Jeff B., et al.. (2012). Visualinguistic Approach to Medical Image Understanding.. AMIA. 2 indexed citations
11.
Shi, Pengcheng, et al.. (2012). Perceptual space asymmetry above and below the eye level reveals ground superiority in the reduced cue environment. Journal of Vision. 12(9). 914–914. 1 indexed citations
12.
Pelz, Jeff B., et al.. (2012). Learning Image-Derived Eye Movement Patterns to Characterize Perceptual Expertise. Cognitive Science. 34(34). 7 indexed citations
13.
Lu, Zhentai, Qianjin Feng, Pengcheng Shi, & Wufan Chen. (2007). A Fast 3-D Medical Image Registration Algorithm Based on Equivalent Meridian Plane. 2. V – 357. 6 indexed citations
14.
Wong, Ken C. L., et al.. (2007). Integrating Functional and Structural Images for Simultaneous Cardiac Segmentation and Deformation Recovery. Lecture notes in computer science. 10(Pt 1). 270–277. 3 indexed citations
15.
Liu, Huafeng, et al.. (2005). Meshfree Cardiac Motion Analysis Framework Using Composite Material Model and Total Lagrangian Formulation. International Conference on Image Processing. 1 indexed citations
16.
Liu, Huafeng, et al.. (2004). Spatiotemporal Curve Evolution for Simultaneous Shape and Motion Recovery. 1 indexed citations
17.
Wong, Albert Kai-Sun, Pengcheng Shi, Huafeng Liu, & Albert J. Sinusas. (2004). Joint analysis of heart geometry and kinematics with spatiotemporal active region model. 762–765. 3 indexed citations
18.
Shi, Pengcheng, et al.. (2002). Peg-free hand geometry recognition using hierarchical geometry and shape matching. 281–284. 59 indexed citations
19.
Liu, Huafeng, et al.. (2002). Velocity Field Constrained Front Propagation for Segmentation of Cardiac Images. 1 indexed citations
20.
Shi, Pengcheng, Albert J. Sinusas, R. Todd Constable, & James S. Duncan. (1999). Volumetric Deformation Analysis Using Mechanics-Based Data Fusion: Applications in Cardiac Motion Recovery. International Journal of Computer Vision. 35(1). 87–107. 45 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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