Sheng-Yu Wang

1.3k total citations · 1 hit paper
14 papers, 702 citations indexed

About

Sheng-Yu Wang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Sheng-Yu Wang has authored 14 papers receiving a total of 702 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Vision and Pattern Recognition, 4 papers in Artificial Intelligence and 2 papers in Computer Networks and Communications. Recurrent topics in Sheng-Yu Wang's work include Generative Adversarial Networks and Image Synthesis (6 papers), Advanced MIMO Systems Optimization (2 papers) and Cognitive Radio Networks and Spectrum Sensing (2 papers). Sheng-Yu Wang is often cited by papers focused on Generative Adversarial Networks and Image Synthesis (6 papers), Advanced MIMO Systems Optimization (2 papers) and Cognitive Radio Networks and Spectrum Sensing (2 papers). Sheng-Yu Wang collaborates with scholars based in United States, China and Australia. Sheng-Yu Wang's co-authors include Richard Zhang, Alexei A. Efros, Oliver Wang, Andrew Owens, Jun-Yan Zhu, Nupur Kumari, David Bau, Eli Shechtman, Bingliang Zhang and Anthony D. Rollett and has published in prestigious journals such as Acta Materialia, Sensors and ACM Transactions on Graphics.

In The Last Decade

Sheng-Yu Wang

11 papers receiving 676 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.

CNN-Generated Images Are Surprisingly Easy to Spot… for Now

2020 541 citations Sheng-Yu Wang, Oliver Wang et al. profile →

Peers

Sheng-Yu Wang

CVPR

AI

SP

MT

BIOPH

Nilaksh Das United States

Wenbo Zhou China

Kaidi Cao United States

Tim Brooks United States

Shagan Sah United States

Grigory Antipov France

Moez Baccouche France

Tianyi Wei China

Jingyan Qin China

Peipei Kang China

Nilaksh Das United States

Sheng-Yu Wang

105 ×0.2

CVPR

155 ×0.8

AI

31 ×0.8

SP

11 ×0.5

MT

11 ×0.5

BIOPH

Citations per year, relative to Sheng-Yu Wang Sheng-Yu Wang (= 1×) peers Nilaksh Das

Countries citing papers authored by Sheng-Yu Wang

Since Specialization

Citations

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

Fields of papers citing papers by Sheng-Yu Wang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sheng-Yu Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Sheng-Yu Wang. A scholar is included among the top collaborators of Sheng-Yu 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 Sheng-Yu Wang. Sheng-Yu Wang 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:

14 of 14 papers shown

1.

Wang, Sheng-Yu, Xin‐Lin Huang, Fei Hu, & Shui Yu. (2025). A Fast-Convergence, Induced Dynamic Spectrum Access Based on Accelerated Q-Learning for Cognitive Radio Networks. IEEE Transactions on Vehicular Technology. 74(9). 13925–13937.

2.

Canavan, Susan, César Capinha, Ana Novoa, et al.. (2025). Sustainability of large language models—user perspective. Frontiers in Ecology and the Environment. 23(5). 1 indexed citations

3.

Wang, Tingting, et al.. (2024). The Research on College Students Physical Fitness Using Machine Learning Algorithm. 12–16.

4.

Wei, Jianhua, et al.. (2024). A machine learning-based hybrid recommender framework for smart medical systems. PeerJ Computer Science. 10. e1880–e1880. 2 indexed citations

5.

Wang, Sheng-Yu, et al.. (2024). Customizing Text-to-Image Models with a Single Image Pair. 1–13. 8 indexed citations

6.

Kumari, Nupur, Bingliang Zhang, Sheng-Yu Wang, et al.. (2023). Ablating Concepts in Text-to-Image Diffusion Models. 22634–22645. 30 indexed citations

7.

Wang, Sheng-Yu, Alexei A. Efros, Jun-Yan Zhu, & Richard Zhang. (2023). Evaluating Data Attribution for Text-to-Image Models. 7158–7169. 6 indexed citations

8.

Wang, Sheng-Yu. (2022). Intelligent Quality Strategic Management Platform with Flow Data Mining and PHP Coding for Smart Higher Education Guiding Optimization. 2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS). 115. 1402–1406.

9.

Wang, Sheng-Yu, David Bau, & Jun-Yan Zhu. (2022). Rewriting geometric rules of a GAN. ACM Transactions on Graphics. 41(4). 1–16. 12 indexed citations

10.

Wang, Sheng-Yu, Oliver Wang, Richard Zhang, Andrew Owens, & Alexei A. Efros. (2020). CNN-Generated Images Are Surprisingly Easy to Spot… for Now. 8692–8701. 541 indexed citations breakdown →

11.

Wang, Sheng-Yu, Oliver Wang, Richard Zhang, Andrew Owens, & Alexei A. Efros. (2019). Detecting Photoshopped Faces by Scripting Photoshop. 10071–10080. 71 indexed citations

12.

Zeng, Biqing, et al.. (2017). Spectrum Sharing Based on a Bertrand Game in Cognitive Radio Sensor Networks. Sensors. 17(1). 101–101. 8 indexed citations

13.

Chen, Wei, et al.. (2011). Human and car identification using motion vector in H.264 compressed video. 1–4. 1 indexed citations

14.

Wang, Sheng-Yu, et al.. (2011). Modeling the recrystallized grain size in single phase materials. Acta Materialia. 59(10). 3872–3882. 22 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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