Xinyue Liu
- Artificial Intelligence top 10%
- Topic Modeling 4
- Natural Language Processing Techniques 3
- Anomaly Detection Techniques and Applications 3
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- Video Surveillance and Tracking Methods 4
- Multimodal Machine Learning Applications 4
- Visual Attention and Saliency Detection 3
- Advanced Neural Network Applications 2
- Information Systems top 10%
- Spam and Phishing Detection 2
- Co-authors
- Runsheng TangZhimin LiYonghwi KwonWeihang WangMenggang LiSaket SatheYu-Feng LiHongfei Lin
- Journals
- SHILAP Revista de lepidopterología (1 paper)Energy (1 paper)IEEE Transactions on Intelligent Transportation Systems (1 paper)
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
Xinyue Liu
21 papers receiving 206 citations
Peers
Comparison fields: 5 of 53
- Artificial Intelligence 129
- Software 15
- Renewable Energy, Sustainability and the Environment 59
- Computer Vision and Pattern Recognition 67
- Information Systems 53
Countries citing papers authored by Xinyue Liu
This map shows the geographic impact of Xinyue Liu'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 Xinyue Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xinyue Liu more than expected).
Fields of papers citing papers by Xinyue Liu
This network shows the impact of papers produced by Xinyue Liu. 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 Xinyue Liu. The network helps show where Xinyue Liu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Xinyue Liu, 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 | 0 | |
| 2 | 2025 | 2 | |
| 3 | 2024 | 0 | |
| 4 | 2024 | 0 | |
| 5 | 2023 | 0 | |
| 6 | 2023 | 1 | |
| 7 | 2022 | 0 | |
| 8 | 2021 | 10 | |
| 9 | 2021 | 28 | |
| 10 | 2021 | 1 | |
| 11 | 2020 | 3 | |
| 12 | 2020 | 5 | |
| 13 | 2019 | 4 | |
| 14 | 2019 | 9 | |
| 15 | 2018 | 11 | |
| 16 | 2014 | 9 | |
| 17 | 2014 | 12 | |
| 18 | 2011 | 8 | |
| 19 | 2011 | 3 | |
| 20 | 2010 | 64 |
About Xinyue Liu
Xinyue Liu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing, having authored 26 papers that have together received 218 indexed citations. Recurring topics across this work include Topic Modeling (4 papers), Video Surveillance and Tracking Methods (4 papers), Multimodal Machine Learning Applications (4 papers), Visual Attention and Saliency Detection (3 papers), Natural Language Processing Techniques (3 papers), Anomaly Detection Techniques and Applications (3 papers), Spam and Phishing Detection (2 papers) and Advanced Neural Network Applications (2 papers). The work is most often cited by research in Artificial Intelligence (129 citations), Software (15 citations) and Renewable Energy, Sustainability and the Environment (59 citations). Xinyue Liu has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Runsheng Tang, Zhimin Li, Yonghwi Kwon, Weihang Wang, Menggang Li, Saket Sathe, Yu-Feng Li, Hongfei Lin, Xiangnan Kong and Kuorong Chiang. Their work appears in journals such as SHILAP Revista de lepidopterología, Energy and IEEE Transactions on Intelligent Transportation Systems.
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.