Shuo Wang

2.6k total citations · 2 hit papers
114 papers, 1.4k citations indexed

About

Shuo Wang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Environmental Engineering. According to data from OpenAlex, Shuo Wang has authored 114 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Computer Vision and Pattern Recognition, 15 papers in Artificial Intelligence and 10 papers in Environmental Engineering. Recurrent topics in Shuo Wang's work include Visual Attention and Saliency Detection (8 papers), Image Enhancement Techniques (8 papers) and Video Surveillance and Tracking Methods (6 papers). Shuo Wang is often cited by papers focused on Visual Attention and Saliency Detection (8 papers), Image Enhancement Techniques (8 papers) and Video Surveillance and Tracking Methods (6 papers). Shuo Wang collaborates with scholars based in China, United States and Switzerland. Shuo Wang's co-authors include Tian-Zhu Xiang, Chenglizhao Chen, Yujia Sun, Hang Dai, Huan Xiong, Jie Qin, Zhou Huang, Huaixin Chen, Zongwei Wu and Cédric Demonceaux and has published in prestigious journals such as Journal of Neuroscience, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Shuo Wang

98 papers receiving 1.3k citations

Hit Papers

Boundary-Guided Camouflaged Object Detection 2022 2026 2023 2024 2022 2023 50 100 150
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.

  1. Boundary-Guided Camouflaged Object Detection
    2022 158 citations Shuo Wang, Tian-Zhu Xiang et al. profile →
  2. Feature Shrinkage Pyramid for Camouflaged Object Detection with Transformers
    2023 119 citations Tian-Zhu Xiang, Shuo Wang et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shuo Wang China 19 487 124 105 102 98 114 1.4k
Yuanyuan Liu China 22 456 0.9× 138 1.1× 161 1.5× 86 0.8× 40 0.4× 96 1.6k
Li Zheng China 18 229 0.5× 86 0.7× 138 1.3× 133 1.3× 51 0.5× 67 912
Niannian Wang China 29 244 0.5× 148 1.2× 80 0.8× 39 0.4× 43 0.4× 137 2.4k
Min Young Kim South Korea 27 499 1.0× 82 0.7× 68 0.6× 38 0.4× 187 1.9× 192 2.1k
Yao Sun China 15 131 0.3× 211 1.7× 89 0.8× 97 1.0× 39 0.4× 57 752
Ashwani Kumar Aggarwal India 20 290 0.6× 110 0.9× 251 2.4× 126 1.2× 30 0.3× 47 1.2k
Fei Wang China 20 396 0.8× 186 1.5× 325 3.1× 192 1.9× 25 0.3× 141 1.6k
Shuang Liu China 25 643 1.3× 120 1.0× 261 2.5× 289 2.8× 207 2.1× 165 2.2k
Cheng Shi China 23 646 1.3× 96 0.8× 187 1.8× 133 1.3× 94 1.0× 100 1.8k

Countries citing papers authored by Shuo Wang

Since Specialization
Citations

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

Fields of papers citing papers by Shuo Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shuo Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Shuo Wang. A scholar is included among the top collaborators of Shuo 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 Shuo Wang. Shuo 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.
Gao, Yansong, Hua Ma, Zhi Zhang, et al.. (2025). Try to Poison My Deep Learning Data? Nowhere to Hide Your Trajectory Spectrum!. UWA Profiles and Research Repository (UWA). 1 indexed citations
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Ding, Yong, et al.. (2025). A Lightweight Decentralized Federated Learning Framework for the Industrial Internet of Things. Ad Hoc Networks. 178. 103962–103962.
5.
Cao, Yichuan, et al.. (2024). Smartphone-assisted ratiometric fluorescent sensor for visual detection of chlortetracycline. Food Chemistry. 460(Pt 3). 140774–140774. 13 indexed citations
6.
Zheng, Zhenhui, Ling Chen, Chenglin Wang, et al.. (2024). A robust and efficient citrus counting approach for large-scale unstructured orchards. Agricultural Systems. 215. 103867–103867. 8 indexed citations
7.
Wu, Shijun, et al.. (2024). A review of deep-seawater samplers: Principles, applications, performance, and trends. Deep Sea Research Part I Oceanographic Research Papers. 213. 104401–104401. 1 indexed citations
8.
Wang, Shuo, et al.. (2024). Sharing asymmetric Einstein–Podolsky–Rosen steering with projective measurements. New Journal of Physics. 26(8). 83014–83014. 2 indexed citations
9.
Zhou, Qian, Jialong Jie, Shuo Wang, et al.. (2024). Dual Functionality of 6-Methylthioguanine: Synergistic Effects Enhancing the Photolability of DNA Nucleobases. SHILAP Revista de lepidopterología. 4(2). 441–453. 1 indexed citations
10.
Li, Siwei, Jie Yang, Shuo Wang, et al.. (2023). Long-term PM2.5 concentration prediction based on improved empirical mode decomposition and deep neural network combined with noise reduction auto-encoder- A case study in Beijing. Journal of Cleaner Production. 428. 139449–139449. 10 indexed citations
11.
Zhang, Shuai, et al.. (2023). Recursive surrogate model based on generalized regression neural network. Applied Soft Computing. 145. 110576–110576. 8 indexed citations
12.
Song, Xueguan, et al.. (2023). DADOS: A Cloud-based Data-driven Design Optimization System. Chinese Journal of Mechanical Engineering. 36(1). 5 indexed citations
13.
Wang, Shuo, et al.. (2023). An Image Object Detection Model Based on Mixed Attention Mechanism Optimized YOLOv5. Electronics. 12(7). 1515–1515. 10 indexed citations
14.
Wang, Shuo, et al.. (2023). Hyperspectral Image Restoration via a New Symmetric ADMM Approach. Mathematical Problems in Engineering. 2023(1).
15.
Li, Xin & Shuo Wang. (2023). Toward a computational theory of manifold untangling: from global embedding to local flattening. Frontiers in Computational Neuroscience. 17. 1197031–1197031. 1 indexed citations
16.
Zheng, Peng, Jie Qin, Shuo Wang, Tian-Zhu Xiang, & Huan Xiong. (2023). Memory-Aided Contrastive Consensus Learning for Co-salient Object Detection. Proceedings of the AAAI Conference on Artificial Intelligence. 37(3). 3687–3695. 15 indexed citations
17.
Wang, Shuo, et al.. (2022). Modified Multifidelity Surrogate Model Based on Radial Basis Function with Adaptive Scale Factor. Chinese Journal of Mechanical Engineering. 35(1). 12 indexed citations
18.
Wang, Shuo, Liuqing Chen, Chao Wu, et al.. (2020). Neurocognition-inspired design with machine learning. Design Science. 6. 14 indexed citations
19.
Wang, Shuo, Zhang Zhang, Xiao Lin, et al.. (2009). A polysaccharide, MDG-1, induces S1P1 and bFGF expression and augments survival and angiogenesis in the ischemic heart. Glycobiology. 20(4). 473–484. 41 indexed citations
20.
Yılmaz, Levent & Shuo Wang. (2005). Integrating Model-Based Verification into Software Design Education. Journal of STEM education. 6(3). 29–34. 2 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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