Shuchang Zhou

5.8k total citations
33 papers, 662 citations indexed

About

Shuchang Zhou is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Shuchang Zhou has authored 33 papers receiving a total of 662 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Computer Vision and Pattern Recognition, 9 papers in Artificial Intelligence and 4 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Shuchang Zhou's work include Advanced Neural Network Applications (8 papers), Generative Adversarial Networks and Image Synthesis (5 papers) and Human Pose and Action Recognition (5 papers). Shuchang Zhou is often cited by papers focused on Advanced Neural Network Applications (8 papers), Generative Adversarial Networks and Image Synthesis (5 papers) and Human Pose and Action Recognition (5 papers). Shuchang Zhou collaborates with scholars based in China, United States and India. Shuchang Zhou's co-authors include Wen Heng, Zhewei Huang, Yang Chen, Li Xiao, Zheng Li, Tianyu Zhang, Zhewei Huang, Anne L. Martel, Daniel Racoceanu and Diana Mateus and has published in prestigious journals such as Construction and Building Materials, Neural Networks and Radiotherapy and Oncology.

In The Last Decade

Shuchang Zhou

26 papers receiving 648 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shuchang Zhou China 13 388 190 110 67 59 33 662
Ning Xu China 13 529 1.4× 120 0.6× 89 0.8× 41 0.6× 30 0.5× 53 816
Anne C. Elster Norway 10 192 0.5× 96 0.5× 87 0.8× 39 0.6× 24 0.4× 50 501
Yan Xia China 15 322 0.8× 74 0.4× 104 0.9× 33 0.5× 40 0.7× 52 661
Itsuo Kumazawa Japan 10 206 0.5× 106 0.6× 82 0.7× 28 0.4× 26 0.4× 101 512
Jizhao Liu China 15 234 0.6× 106 0.6× 35 0.3× 63 0.9× 20 0.3× 46 607
Byung‐Woo Hong South Korea 15 461 1.2× 185 1.0× 130 1.2× 22 0.3× 12 0.2× 64 766
S.B. Gokturk United States 11 601 1.5× 122 0.6× 150 1.4× 50 0.7× 15 0.3× 18 874
Hiroshi Nagahashi Japan 12 256 0.7× 146 0.8× 51 0.5× 21 0.3× 42 0.7× 87 606
Leiting Chen China 14 330 0.9× 228 1.2× 131 1.2× 15 0.2× 14 0.2× 99 674

Countries citing papers authored by Shuchang Zhou

Since Specialization
Citations

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

Fields of papers citing papers by Shuchang Zhou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shuchang Zhou

This figure shows the co-authorship network connecting the top 25 collaborators of Shuchang Zhou. A scholar is included among the top collaborators of Shuchang Zhou 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 Shuchang Zhou. Shuchang Zhou 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.
Zhou, Shuchang, et al.. (2025). PIDSR: Complementary Polarized Image Demosaicing and Super-Resolution. 16081–16090.
2.
Li, Bohan, J. Guo, Xiwu Chen, et al.. (2025). UniScene: Unified Occupancy-centric Driving Scene Generation. 11971–11981. 1 indexed citations
3.
Yuan, Song, et al.. (2025). Arch-Net: Model conversion and quantization for architecture agnostic model deployment. Neural Networks. 187. 107384–107384.
4.
5.
Wu, Tingting, et al.. (2024). Medical image reconstruction with multi-level deep learning denoiser and tight frame regularization. Applied Mathematics and Computation. 477. 128795–128795. 4 indexed citations
6.
Huang, Zhewei, et al.. (2024). Scale-Adaptive Feature Aggregation for Efficient Space-Time Video Super-Resolution. 4216–4227. 10 indexed citations
7.
8.
Wang, Heng, et al.. (2023). One Is All: Bridging the Gap between Neural Radiance Fields Architectures with Progressive Volume Distillation. Proceedings of the AAAI Conference on Artificial Intelligence. 37(1). 597–605. 7 indexed citations
9.
10.
Zhou, Shuchang, et al.. (2023). Three Guidelines You Should Know for Universally Slimmable Self-Supervised Learning. 15742–15751. 3 indexed citations
11.
Zhou, Shuchang, et al.. (2021). VIBRATION-BASED DAMAGE IDENTIFICATION OF REINFORCED CONCRETE ARCH BRIDGES USING KALMAN–ARMA–GARCH MODEL. International Journal of Robotics and Automation. 36(10). 2 indexed citations
12.
Xiao, Li, et al.. (2021). Marginal loss and exclusion loss for partially supervised multi-organ segmentation. Medical Image Analysis. 70. 101979–101979. 79 indexed citations
13.
Shen, Zengming, et al.. (2020). One-to-one Mapping for Unpaired Image-to-image Translation. 1159–1168. 13 indexed citations
14.
Martel, Anne L., Purang Abolmaesumi, Danail Stoyanov, et al.. (2020). Medical Image Computing and Computer Assisted Intervention – MICCAI 2020. Lecture notes in computer science. 91 indexed citations
15.
Huang, Zhewei, Wen Heng, & Shuchang Zhou. (2019). Stroke-based Artistic Rendering Agent with Deep Reinforcement Learning. arXiv (Cornell University). 1 indexed citations
16.
Huang, Zhewei, Shuchang Zhou, & Wen Heng. (2019). Learning to Paint With Model-Based Deep Reinforcement Learning. 8708–8717. 86 indexed citations
17.
Zhou, Shuchang, et al.. (2017). GeneGAN: Learning Object Transfiguration and Object Subspace from Unpaired Data. 41 indexed citations
18.
Li, Fangtao, et al.. (2013). Deceptive Answer Prediction with User Preference Graph. Meeting of the Association for Computational Linguistics. 1723–1732. 3 indexed citations
19.
Peng, Haoruo, et al.. (2013). A scalable approach to column-based low-rank matrix approximation. International Joint Conference on Artificial Intelligence. 1600–1606. 4 indexed citations
20.
Zhou, Shuchang, Wenyi Zhao, Xiaoou Tang, & Shaogang Gong. (2007). Analysis and Modeling of Faces and Gestures : Third International Workshop, AMFG 2007, Rio de Janeiro, Brazil, October 20, 2007 : proceedings. DIAL (Catholic University of Leuven).

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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