Xiaohui Cui
- Artificial Intelligence top 1%
- Anomaly Detection Techniques and Applications 19
- Topic Modeling 15
- Adversarial Robustness in Machine Learning 11
- Media Technology top 1%
- Information Systems top 1%
- Blockchain Technology Applications and Security 17
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- Digital Media Forensic Detection 15
- Generative Adversarial Networks and Image Synthesis 11
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- Network Security and Intrusion Detection 11
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- Complex Network Analysis Techniques 19
- Partner nations
- ChinaUnited StatesNew Zealand
In The Last Decade
Xiaohui Cui
181 papers receiving 2.9k citations
Hit Papers
Peers
Comparison fields: 5 of 157
- Artificial Intelligence 1.1k
- Media Technology 291
- Information Systems 634
- Computer Vision and Pattern Recognition 556
- Computer Networks and Communications 521
Countries citing papers authored by Xiaohui Cui
This map shows the geographic impact of Xiaohui Cui'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 Xiaohui Cui with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaohui Cui more than expected).
Fields of papers citing papers by Xiaohui Cui
This network shows the impact of papers produced by Xiaohui Cui. 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 Xiaohui Cui. The network helps show where Xiaohui Cui may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Xiaohui Cui, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 4 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 6 | |
| 4 | 2024 | 10 | |
| 5 | 2024 | 12 | |
| 6 | 2024 | 11 | |
| 7 | 2024 | 1 | |
| 8 | 2024 | 1 | |
| 9 | 2024 | 13 | |
| 10 | 2024 | 27 | |
| 11 | 2023 | 2 | |
| 12 | 2023 | 2 | |
| 13 | 2022 | 8 | |
| 14 | 2021 | 23 | |
| 15 | 2021 | 17 | |
| 16 | 2021 | 9 | |
| 17 | 2021 | 7 | |
| 18 | 2021 | 20 | |
| 19 | Inspect Characteristics of Rice via Machine Learning Method. | 2020 | 1 |
| 20 | 2019 | 41 |
About Xiaohui Cui
Xiaohui Cui is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Statistical and Nonlinear Physics and Signal Processing, having authored 198 papers that have together received 3.0k indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (19 papers), Complex Network Analysis Techniques (19 papers), Blockchain Technology Applications and Security (17 papers), Topic Modeling (15 papers), Digital Media Forensic Detection (15 papers), Adversarial Robustness in Machine Learning (11 papers), Network Security and Intrusion Detection (11 papers) and Generative Adversarial Networks and Image Synthesis (11 papers). The work is most often cited by research in Artificial Intelligence (1.1k citations), Media Technology (291 citations), Information Systems (634 citations), Computer Vision and Pattern Recognition (556 citations) and Computer Networks and Communications (521 citations). Xiaohui Cui has collaborated with scholars based in China, United States and New Zealand. Frequent co-authors include Thomas E. Potok, Hongwei Ding, Wei Li, Adnan Iftekhar, Bo Du, Chen Wu, Liangpei Zhang, Qi Tao, Zhidong Shen and Chao Ma. Their work appears in journals such as Foods, Information Sciences, IEEE Access, Knowledge-Based Systems and Personal and Ubiquitous Computing.
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.