Zhengwei Wang
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 5%
- Biomedical Engineering
- Signal Processing top 10%
- Cognitive Neuroscience
- Co-authors
- Qi SheTomás WardAljoša SmolićEoin BrophyGraham HealyAlan F. SmeatonZhigang LiuXuesong Shi
- Topics
- Generative Adversarial Networks and Image Synthesis (5 papers)EEG and Brain-Computer Interfaces (5 papers)Neural dynamics and brain function (4 papers)
- Journals
- SHILAP Revista de lepidopterologíaACM Computing SurveysPattern Recognition
In The Last Decade
Zhengwei Wang
24 papers receiving 669 citations
Hit Papers
Peers
Comparison fields: 5 of 108
- Computer Vision and Pattern Recognition 337
- Artificial Intelligence 283
- Biomedical Engineering 86
- Signal Processing 73
- Cognitive Neuroscience 59
Countries citing papers authored by Zhengwei Wang
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
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
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 6 | |
| 4 | Generative Adversarial Networks in Time Series: A Systematic Literature Reviewbreakdown → | 178 |
| 5 | 19 | |
| 6 | 4 | |
| 7 | 23 | |
| 8 | 9 | |
| 9 | 144 | |
| 10 | 163 | |
| 11 | 0 | |
| 12 | 5 | |
| 13 | 39 | |
| 14 | 0 | |
| 15 | Generative Adversarial Networks: A Survey and Taxonomy. | 33 |
| 16 | Neuroscore: A Brain-inspired Evaluation Metric for Generative Adversarial Networks | 5 |
| 17 | OpenLORIS-Object: A Dataset and Benchmark towards Lifelong Object Recognition | 5 |
| 18 | 7 | |
| 19 | 14 | |
| 20 | 8 |
About Zhengwei Wang
Zhengwei Wang is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction and Artificial Intelligence, having authored 26 papers that have together received 688 indexed citations. Recurring topics across this 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). The work is most often cited by research in Computer Vision and Pattern Recognition (337 citations), Human-Computer Interaction (52 citations) and Artificial Intelligence (283 citations). Zhengwei Wang has collaborated with scholars based in Ireland, China and Hong Kong. Frequent co-authors include Qi She, Tomás Ward, Aljoša Smolić, Eoin Brophy, Graham Healy, Alan F. Smeaton, Zhigang Liu, Xuesong Shi, Rosa H. M. Chan and Vincenzo Lomonaco. Their work appears in journals such as SHILAP Revista de lepidopterología, ACM Computing Surveys and Pattern Recognition.
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.