Zhengwei Wang

1.5k total citations · 1 hit paper
26 papers, 688 citations indexed

About

Zhengwei Wang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Cognitive Neuroscience. According to data from OpenAlex, Zhengwei Wang has authored 26 papers receiving a total of 688 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Computer Vision and Pattern Recognition, 10 papers in Artificial Intelligence and 6 papers in Cognitive Neuroscience. Recurrent topics in Zhengwei Wang's work include Generative Adversarial Networks and Image Synthesis (5 papers), EEG and Brain-Computer Interfaces (5 papers) and Neural dynamics and brain function (4 papers). Zhengwei Wang is often cited by papers focused on Generative Adversarial Networks and Image Synthesis (5 papers), EEG and Brain-Computer Interfaces (5 papers) and Neural dynamics and brain function (4 papers). Zhengwei Wang collaborates with scholars based in Ireland, China and Hong Kong. Zhengwei Wang's co-authors include Qi She, Tomás Ward, Aljoša Smolić, Eoin Brophy, Alan F. Smeaton, Graham Healy, Zhigang Liu, Hongyu Yang, Fei Qiao and Yuzhen Li and has published in prestigious journals such as SHILAP Revista de lepidopterología, ACM Computing Surveys and Pattern Recognition.

In The Last Decade

Zhengwei Wang

24 papers receiving 669 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.

Generative Adversarial Networks in Time Series: A Systematic Literature Review

2022 178 citations Eoin Brophy, Zhengwei Wang et al. ACM Computing Surveys profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Zhengwei Wang Ireland	10	337	283	86	73	59	26	688
Avinash G. Keskar India	17	482 1.4×	318 1.1×	115 1.3×	84 1.2×	65 1.1×	109	1.1k
Kaoru Hirota Japan	16	328 1.0×	272 1.0×	58 0.7×	57 0.8×	39 0.7×	76	827
Jingyong Su China	16	525 1.6×	218 0.8×	153 1.8×	50 0.7×	44 0.7×	56	825
Farbod Razzazi Iran	15	365 1.1×	236 0.8×	57 0.7×	174 2.4×	31 0.5×	111	693
Munif Alotaibi Saudi Arabia	15	266 0.8×	248 0.9×	157 1.8×	92 1.3×	23 0.4×	32	736
M. Cevdet İnce Türkiye	9	270 0.8×	392 1.4×	138 1.6×	37 0.5×	61 1.0×	25	808
Bowen Du China	14	220 0.7×	189 0.7×	98 1.1×	70 1.0×	37 0.6×	50	827
Peiguang Jing China	16	706 2.1×	296 1.0×	68 0.8×	65 0.9×	45 0.8×	92	1.1k
Bo Xiong United States	15	980 2.9×	412 1.5×	80 0.9×	76 1.0×	21 0.4×	23	1.3k

Countries citing papers authored by Zhengwei Wang

Since Specialization

Citations

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

Fields of papers citing papers by Zhengwei Wang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhengwei Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Zhengwei Wang. A scholar is included among the top collaborators of Zhengwei 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 Zhengwei Wang. Zhengwei Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Wang, Zhengwei, et al.. (2025). Review of the development status of low-code programming software for robots. 4. 100039–100039. 1 indexed citations

Wang, Yingfeng, et al.. (2024). 3D Human Pose Estimation with Two-step Mixed-Training Strategy. 3320–3329. 1 indexed citations

Gao, Pan, et al.. (2023). SalDA: DeepConvNet Greets Attention for Visual Saliency Prediction. IEEE Transactions on Cognitive and Developmental Systems. 16(1). 319–331. 6 indexed citations

Brophy, Eoin, Zhengwei Wang, Qi She, & Tomás Ward. (2022). Generative Adversarial Networks in Time Series: A Systematic Literature Review. ACM Computing Surveys. 55(10). 1–31. 178 indexed citations breakdown →

Wang, Zhengwei, et al.. (2022). VECTOR: Very deep convolutional autoencoders for non‐resonant background removal in broadband coherent anti‐Stokes Raman scattering. Journal of Raman Spectroscopy. 53(6). 1081–1093. 19 indexed citations

Liu, Qi, Qi She, Vincenzo Lomonaco, et al.. (2022). Towards lifelong object recognition: A dataset and benchmark. Pattern Recognition. 130. 108819–108819. 4 indexed citations

Liu, Zhigang, et al.. (2022). An Adaptive Specific Emitter Identification System for Dynamic Noise Domain. IEEE Internet of Things Journal. 9(24). 25117–25135. 23 indexed citations

Wang, Zhengwei, et al.. (2022). Institution Publication Feature Analysis Based on Time-Series Clustering. Entropy. 24(7). 950–950. 1 indexed citations

Wang, Zhengwei, Qi She, & Tomás Ward. (2021). Generative Adversarial Networks in Computer Vision. ACM Computing Surveys. 54(2). 1–38. 144 indexed citations

10.

Wang, Zhengwei, et al.. (2021). TEAM-Net: Multi-modal Learning for Video Action Recognition with Partial Decoding.

11.

Wang, Zhengwei, Qi She, & Aljoša Smolić. (2021). ACTION-Net: Multipath Excitation for Action Recognition. 13209–13218. 163 indexed citations

12.

Wang, Zhengwei, Qi She, Alan F. Smeaton, Tomás Ward, & Graham Healy. (2020). Synthetic-Neuroscore: Using a neuro-AI interface for evaluating generative adversarial networks. Neurocomputing. 405. 26–36. 5 indexed citations

13.

Wang, Zhengwei, et al.. (2020). CatNet: Class Incremental 3D ConvNets for Lifelong Egocentric Gesture Recognition. Trinity's Access to Research Output (TARA) (Trinity College Dublin). 935–944. 8 indexed citations

14.

Wang, Zhengwei, Qi She, Alan F. Smeaton, Tomás Ward, & Graham Healy. (2019). Neuroscore: A Brain-inspired Evaluation Metric for Generative Adversarial Networks. arXiv (Cornell University). 5 indexed citations

15.

Wang, Zhengwei, Qi She, & Tomás Ward. (2019). Generative Adversarial Networks: A Survey and Taxonomy.. arXiv (Cornell University). 33 indexed citations

16.

She, Qi, Vincenzo Lomonaco, Xuesong Shi, et al.. (2019). OpenLORIS-Object: A Dataset and Benchmark towards Lifelong Object Recognition. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 5 indexed citations

17.

Wang, Zhengwei, Graham Healy, Alan F. Smeaton, & Tomás Ward. (2018). Spatial filtering pipeline evaluation of cortically coupled computer vision system for rapid serial visual presentation. arXiv (Cornell University). 5(4). 132–145. 7 indexed citations

18.

Wang, Zhengwei, Graham Healy, Alan F. Smeaton, & Tomás Ward. (2018). A review of feature extraction and classification algorithms for image RSVP-based BCI. Institution of Engineering and Technology eBooks. 243–270. 14 indexed citations

19.

Wang, Zhengwei, et al.. (2018). Validation of low-cost wireless EEG system for measuring event-related potentials. 1–6. 8 indexed citations

20.

Wang, Zhengwei, Graham Healy, Alan F. Smeaton, & Tomás Ward. (2016). An investigation of triggering approaches for the rapid serial visual presentation paradigm in brain computer interfacing. 1–6. 9 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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