Shuang Wu

1.0k total citations · 1 hit paper
36 papers, 656 citations indexed

About

Shuang Wu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Shuang Wu has authored 36 papers receiving a total of 656 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Computer Vision and Pattern Recognition, 9 papers in Artificial Intelligence and 6 papers in Signal Processing. Recurrent topics in Shuang Wu's work include Video Analysis and Summarization (10 papers), Video Surveillance and Tracking Methods (9 papers) and Human Pose and Action Recognition (8 papers). Shuang Wu is often cited by papers focused on Video Analysis and Summarization (10 papers), Video Surveillance and Tracking Methods (9 papers) and Human Pose and Action Recognition (8 papers). Shuang Wu collaborates with scholars based in China, United States and Canada. Shuang Wu's co-authors include Xiaodan Zhuang, Bo Li, Shouhong Ding, Lv Tang, Prem Natarajan, Pradeep Natarajan, Stavros Tsakalidis, Shiv Vitaladevuni, Unsang Park and Ramendra Prasad and has published in prestigious journals such as Communications of the ACM, Expert Systems with Applications and Pattern Recognition.

In The Last Decade

Shuang Wu

32 papers receiving 641 citations

Hit Papers

Detecting Camouflaged Object in Frequency Domain 2022 2026 2023 2024 2022 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. Detecting Camouflaged Object in Frequency Domain
    2022 172 citations Shuang Wu 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
Shuang Wu China 13 474 147 60 53 41 36 656
Xuansong Xie China 17 790 1.7× 141 1.0× 32 0.5× 42 0.8× 87 2.1× 50 957
Yunfan Liu China 13 563 1.2× 163 1.1× 28 0.5× 65 1.2× 23 0.6× 38 780
Antoine Manzanera France 10 337 0.7× 45 0.3× 34 0.6× 16 0.3× 31 0.8× 37 453
Jingchun Cheng China 8 478 1.0× 73 0.5× 22 0.4× 15 0.3× 36 0.9× 23 607
Sabina Umirzakova South Korea 14 250 0.5× 103 0.7× 47 0.8× 9 0.2× 54 1.3× 55 506
Ramsha Ahmed China 13 195 0.4× 75 0.5× 76 1.3× 33 0.6× 23 0.6× 26 578
Xiaolong Jiang China 11 522 1.1× 264 1.8× 10 0.2× 18 0.3× 68 1.7× 30 655
Xingfang Yuan China 4 271 0.6× 104 0.7× 36 0.6× 49 0.9× 25 0.6× 6 433

Countries citing papers authored by Shuang Wu

Since Specialization
Citations

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

Fields of papers citing papers by Shuang Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shuang Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Shuang Wu. A scholar is included among the top collaborators of Shuang Wu 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 Shuang Wu. Shuang Wu 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.
Wu, Shuang, Yu Bo, Shaoshan Liu, & Yuhao Zhu. (2025). Autonomy 2.0: The Quest for Economies of Scale. Communications of the ACM. 68(4). 28–32.
2.
Wu, Shuang, Guangjian Zhang, & Xuefeng Liu. (2024). SwinSOD: Salient object detection using swin-transformer. Image and Vision Computing. 146. 105039–105039. 7 indexed citations
3.
Luo, Yang, Lu Liu, Hongjing Zhang, et al.. (2023). ExpertNet: Defeat noisy labels by deep expert consultation paradigm for pneumoconiosis staging on chest radiographs. Expert Systems with Applications. 232. 120710–120710. 4 indexed citations
4.
Luo, Yang, Lu Liu, Hongjing Zhang, et al.. (2022). A Fully Deep Learning Paradigm for Pneumoconiosis Staging on Chest Radiographs. IEEE Journal of Biomedical and Health Informatics. 26(10). 5154–5164. 18 indexed citations
5.
Wu, Shuang, et al.. (2022). Using Multi-Task Learning-Based Framework to Detect ST-Segment and J-Point Deviation From Holter. Frontiers in Physiology. 13. 912739–912739. 2 indexed citations
6.
Xu, Jun, Rongguo Zhang, Zijian Zhou, et al.. (2021). Deep Network for the Automatic Segmentation and Quantification of Intracranial Hemorrhage on CT. Frontiers in Neuroscience. 14. 541817–541817. 43 indexed citations
7.
Cao, Yangjie, Shuang Wu, Chang Liu, et al.. (2021). Seg-CapNet: A Capsule-Based Neural Network for the Segmentation of Left Ventricle from Cardiac Magnetic Resonance Imaging. Journal of Computer Science and Technology. 36(2). 323–333. 5 indexed citations
8.
Zhao, Qijun, et al.. (2020). Improved Single Sample Per Person Face Recognition via Enriching Intra-Variation and Invariant Features. Applied Sciences. 10(2). 601–601. 6 indexed citations
9.
He, Tingting, et al.. (2018). Application research of image recognition technology based on CNN in image location of environmental monitoring UAV. EURASIP Journal on Image and Video Processing. 2018(1). 18 indexed citations
10.
Wang, Jie, Yaru Yu, Shuang Wu, Xiao Zheng, & Dongping He. (2017). Identification of peanut oil based on feature layer spectral data fusion method. 1 indexed citations
11.
Yang, Hua, et al.. (2017). Deep Spatial-Temporal Fusion Network for Video-Based Person Re-identification. 1478–1485. 20 indexed citations
12.
Yang, Hua, et al.. (2015). Hierarchical video summarization with loitering indication. 5 indexed citations
13.
Wu, Shuang, et al.. (2014). Zero-Shot Event Detection Using Multi-modal Fusion of Weakly Supervised Concepts. 2665–2672. 79 indexed citations
14.
Lu, Xiaowei, Hua Yang, Hang Su, & Shuang Wu. (2014). Flux based pedestrian flow estimation in occluded scenes. 1–5. 1 indexed citations
15.
Natarajan, Pradeep, Shuang Wu, Florian Luisier, et al.. (2013). BBN VISER TRECVID 2013 Multimedia Event Detection and Multimedia Event Recounting Systems. Journal of International Crisis and Risk Communication Research. 14 indexed citations
16.
Natarajan, Pradeep, Prem Natarajan, Shuang Wu, et al.. (2012). BBNVISER : BBN VISER TRECVID 2012 Multimedia Event Detection and Multimedia Event Recounting Systems.. TRECVID. 13 indexed citations
17.
Natarajan, Prem, Shuang Wu, Shiv Vitaladevuni, et al.. (2012). Multimodal feature fusion for robust event detection in web videos. 1298–1305. 132 indexed citations
18.
Zhuang, Xiaodan, Stavros Tsakalidis, Shuang Wu, et al.. (2012). Compact audio representation for event detection in consumer media. 2089–2092. 13 indexed citations
19.
Natarajan, Pradeep, Prem Natarajan, Shuang Wu, et al.. (2011). BBN VISER TRECVID 2011 Multimedia Event Detection System. Journal of International Crisis and Risk Communication Research. 25 indexed citations
20.
Wu, Shuang, Xuming He, Hongjing Lu, & Alan Yuille. (2010). A unified model of short-range and long-range motion perception. Neural Information Processing Systems. 23. 2478–2486. 7 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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