Li Ren
-
- Multimodal Machine Learning Applications 7
- Advanced Image and Video Retrieval Techniques 3
- Face recognition and analysis 2
- Artificial Intelligence top 10%
- Topic Modeling 6
- Natural Language Processing Techniques 5
- Domain Adaptation and Few-Shot Learning 5
- Machine Learning and ELM 2
- Civil and Structural Engineering top 10%
- Infrastructure Maintenance and Monitoring 4
- Co-authors
- Chen Change LoyWayne WuChen QianLiming JiangShixin JiangJianxi YangQiming ZhaoSheng Huang
- Journals
- Expert Systems with Applications (2 papers)Advanced Engineering Informatics (1 paper)IEEE Transactions on Intelligent Transportation Systems (1 paper)
- Partner nations
- ChinaUnited StatesFrance
In The Last Decade
Li Ren
28 papers receiving 492 citations
Hit Papers
Peers
Comparison fields: 5 of 62
- Computer Vision and Pattern Recognition 353
- Artificial Intelligence 170
- Signal Processing 41
- Civil and Structural Engineering 75
- Media Technology 17
Countries citing papers authored by Li Ren
This map shows the geographic impact of Li Ren'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 Li Ren with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Li Ren more than expected).
Fields of papers citing papers by Li Ren
This network shows the impact of papers produced by Li Ren. 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 Li Ren. The network helps show where Li Ren may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Li Ren, 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 | 1 | |
| 2 | 2025 | 2 | |
| 3 | 2025 | 2 | |
| 4 | 2025 | 0 | |
| 5 | 2025 | 1 | |
| 6 | 2024 | 1 | |
| 7 | 2024 | 2 | |
| 8 | 2024 | 0 | |
| 9 | 2024 | 3 | |
| 10 | 2023 | 21 | |
| 11 | 2023 | 0 | |
| 12 | 2023 | 1 | |
| 13 | 2022 | 2 | |
| 14 | 2021 | 45 | |
| 15 | 2020 | 44 | |
| 16 | DeeperForensics-1.0: A Large-Scale Dataset for Real-World Face Forgery Detectionbreakdown → | 2020 | 334 |
| 17 | 2020 | 1 | |
| 18 | A cloud computing based SWRL distributed reasoning framework | 2013 | 1 |
| 19 | Scalable RDF graph querying using cloud computing | 2013 | 3 |
| 20 | 2010 | 2 |
About Li Ren
Li Ren is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Graphics and Computer-Aided Design, having authored 32 papers that have together received 509 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (7 papers), Topic Modeling (6 papers), Natural Language Processing Techniques (5 papers), Domain Adaptation and Few-Shot Learning (5 papers), Infrastructure Maintenance and Monitoring (4 papers), Advanced Image and Video Retrieval Techniques (3 papers), Machine Learning and ELM (2 papers) and Face recognition and analysis (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (353 citations), Artificial Intelligence (170 citations) and Signal Processing (41 citations). Li Ren has collaborated with scholars based in China, United States and France. Frequent co-authors include Chen Change Loy, Wayne Wu, Chen Qian, Liming Jiang, Shixin Jiang, Jianxi Yang, Qiming Zhao, Sheng Huang, Luwen Huangfu and Tong Li. Their work appears in journals such as Expert Systems with Applications, Advanced Engineering Informatics, IEEE Transactions on Intelligent Transportation Systems, Electronics and Engineering Applications of Artificial Intelligence.
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.