Pengcheng Wang

553 total citations
37 papers, 294 citations indexed

About

Pengcheng Wang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Aerospace Engineering. According to data from OpenAlex, Pengcheng Wang has authored 37 papers receiving a total of 294 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Computer Vision and Pattern Recognition, 15 papers in Artificial Intelligence and 7 papers in Aerospace Engineering. Recurrent topics in Pengcheng Wang's work include Advanced Image and Video Retrieval Techniques (5 papers), Robotics and Sensor-Based Localization (5 papers) and Topic Modeling (4 papers). Pengcheng Wang is often cited by papers focused on Advanced Image and Video Retrieval Techniques (5 papers), Robotics and Sensor-Based Localization (5 papers) and Topic Modeling (4 papers). Pengcheng Wang collaborates with scholars based in China, United States and Taiwan. Pengcheng Wang's co-authors include Chung-Ming Wang, James C. Lester, Bradford Mott, Jonathan Rowe, Wookhee Min, Xianghua Wang, Ming Li, Xiangrong Wang, Haiju Fan and Mingwei Tang and has published in prestigious journals such as SHILAP Revista de lepidopterología, Computers in Human Behavior and IEEE Access.

In The Last Decade

Pengcheng Wang

35 papers receiving 280 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 Wang China 11 125 121 39 24 22 37 294
Puneet Kumar India 10 158 1.3× 86 0.7× 48 1.2× 18 0.8× 43 2.0× 29 315
Shuhan Qi China 10 153 1.2× 145 1.2× 13 0.3× 29 1.2× 10 0.5× 49 295
Mei Kuan Lim Malaysia 11 179 1.4× 251 2.1× 12 0.3× 37 1.5× 29 1.3× 30 445
Tengfei Shi China 7 187 1.5× 69 0.6× 17 0.4× 43 1.8× 30 1.4× 15 323
Congcong Li China 10 69 0.6× 283 2.3× 52 1.3× 16 0.7× 21 1.0× 21 341
Chuanyan Hao China 9 74 0.6× 122 1.0× 20 0.5× 31 1.3× 9 0.4× 28 279
Gungor Polatkan United States 8 76 0.6× 152 1.3× 11 0.3× 34 1.4× 19 0.9× 11 294
Lanxiao Huang United States 5 153 1.2× 44 0.4× 17 0.4× 25 1.0× 43 2.0× 7 257
Gregory Kuhlmann United States 8 354 2.8× 61 0.5× 37 0.9× 13 0.5× 11 0.5× 10 423
Wei Shao China 9 237 1.9× 41 0.3× 41 1.1× 66 2.8× 26 1.2× 48 385

Countries citing papers authored by Pengcheng Wang

Since Specialization
Citations

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

Fields of papers citing papers by Pengcheng Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pengcheng Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Pengcheng Wang. A scholar is included among the top collaborators of Pengcheng Wang 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 Wang. Pengcheng Wang 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.
Zhang, Tianyuan, Miao He, Li Geng, et al.. (2024). Smartphone and the brain: Stress and self-control mediate the association between the connectome-based predictive modeling of fMRI brain network and problematic smartphone use. Computers in Human Behavior. 165. 108531–108531. 6 indexed citations
2.
Niu, Yunyun, et al.. (2024). Dynamic Graph Convolutional Recurrent Network With Spatiotemporal Category Information Embedding for Traffic Flow Prediction. IEEE Internet of Things Journal. 11(24). 39473–39486. 1 indexed citations
3.
Diao, Shizhe, et al.. (2024). Active Prompting with Chain-of-Thought for Large Language Models. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 1330–1350. 13 indexed citations
4.
Deng, Jiangzhou, et al.. (2024). A novel joint neural collaborative filtering incorporating rating reliability. Information Sciences. 665. 120406–120406. 9 indexed citations
5.
Wang, Pengcheng, et al.. (2024). MLIOM-AB: Multi-LiDAR-Inertial-Odometry and Mapping for Autonomous Buses. IEEE Sensors Journal. 24(17). 28036–28048. 2 indexed citations
6.
Wang, Pengcheng, et al.. (2024). Incorporating syntax and semantics with dual graph neural networks for aspect-level sentiment analysis. Engineering Applications of Artificial Intelligence. 133. 108101–108101. 13 indexed citations
7.
Yang, Yin, et al.. (2024). Efficient multi-objective neural architecture search framework via policy gradient algorithm. Information Sciences. 661. 120186–120186. 1 indexed citations
8.
Wang, Pengcheng, et al.. (2023). A novel adaptive marker segmentation graph convolutional network for aspect-level sentiment analysis. Knowledge-Based Systems. 270. 110559–110559. 12 indexed citations
9.
Wang, Pengcheng, et al.. (2023). Optimized Polarization Encoder with High Extinction Ratio for Quantum Key Distribution System. Electronics. 12(8). 1859–1859. 1 indexed citations
10.
Wang, Pengcheng, et al.. (2023). Proud of you, so act for you? The role of national pride in promoting individual pro-environmental tendencies. Frontiers in Environmental Science. 11. 4 indexed citations
11.
Yao, Ziying, Xinkai Wu, Pengcheng Wang, & Chuan Ding. (2022). DevNet: Deviation Aware Network for Lane Detection. IEEE Transactions on Intelligent Transportation Systems. 23(10). 17584–17593. 8 indexed citations
12.
Chen, Jianxin, et al.. (2022). Data compression algorithms for sensor networks with periodic transmission schemes. SHILAP Revista de lepidopterología. 355. 3003–3003. 2 indexed citations
13.
Liu, Lan, et al.. (2020). Deep Learning-Based Network Security Data Sampling and Anomaly Prediction in Future Network. Discrete Dynamics in Nature and Society. 2020. 1–9. 12 indexed citations
14.
Wang, Pengcheng, et al.. (2020). Clustering test steps in natural language toward automating test automation. 1285–1295. 7 indexed citations
15.
Wang, Pengcheng, Zihao Wang, Zhilong Ji, et al.. (2020). TAL EmotioNet Challenge 2020 Rethinking the Model Chosen Problem in Multi-Task Learning. 1653–1656. 5 indexed citations
16.
Wang, Pengcheng, Jonathan Rowe, Wookhee Min, Bradford Mott, & James C. Lester. (2017). Simulating Player Behavior for Data-Driven Interactive Narrative Personalization. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 13(1). 255–261. 4 indexed citations
17.
Gu, Yujie, Kan Ren, Pengcheng Wang, & Guohua Gu. (2016). Polynomial fitting-based shape matching algorithm for multi-sensors remote sensing images. Infrared Physics & Technology. 76. 386–392. 10 indexed citations
18.
Yu, Guizhen, et al.. (2015). Measuring Algorithm for the Distance to a Preceding Vehicle on Curve Road Using On-Board Monocular Camera. International Journal of Bifurcation and Chaos. 25(14). 1540038–1540038. 2 indexed citations
19.
Wang, Pengcheng & Chung-Ming Wang. (2007). Reversible data hiding for point-sampled geometry. Journal of information science and engineering. 23(6). 1889–1900. 25 indexed citations
20.
Wang, Pengcheng, et al.. (2006). Data hiding on point‐sampled geometry. Journal of the Chinese Institute of Engineers. 29(3). 539–542. 4 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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