Cheng‐Lin Liu
- Computer Vision and Pattern Recognition top 0.05%
- Handwritten Text Recognition Techniques 187
- Image Retrieval and Classification Techniques 94
- Image Processing and 3D Reconstruction 62
- Advanced Image and Video Retrieval Techniques 58
- Face and Expression Recognition 37
- Media Technology top 0.05%
- Human-Computer Interaction top 0.2%
- Artificial Intelligence top 0.1%
- Natural Language Processing Techniques 48
- Text and Document Classification Technologies 43
- Domain Adaptation and Few-Shot Learning 38
- Signal Processing top 1%
- Co-authors
- Fei YinXu-Yao ZhangCordelia SchmidHeng WangAlexander KläserQiufeng WangHiroshi SakoHiromichi Fujisawa
- Journals
- Environmental Science & Technology (2 papers)PLoS ONE (1 paper)IEEE Transactions on Pattern Analysis and Machine Intelligence (10 papers)
- Partner nations
- ChinaJapanUnited Kingdom
In The Last Decade
Cheng‐Lin Liu
351 papers receiving 12.1k citations
Hit Papers
Peers
Comparison fields: 5 of 200
- Computer Vision and Pattern Recognition 9.7k
- Media Technology 2.3k
- Human-Computer Interaction 886
- Artificial Intelligence 5.0k
- Signal Processing 497
Countries citing papers authored by Cheng‐Lin Liu
This map shows the geographic impact of Cheng‐Lin 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 Cheng‐Lin Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cheng‐Lin Liu more than expected).
Fields of papers citing papers by Cheng‐Lin Liu
This network shows the impact of papers produced by Cheng‐Lin 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 Cheng‐Lin Liu. The network helps show where Cheng‐Lin Liu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Cheng‐Lin 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 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 5 | |
| 5 | 2024 | 0 | |
| 6 | 2024 | 5 | |
| 7 | 2024 | 0 | |
| 8 | 2024 | 0 | |
| 9 | 2024 | 8 | |
| 10 | 2023 | 44 | |
| 11 | 2023 | 3 | |
| 12 | 2023 | 10 | |
| 13 | 2023 | 0 | |
| 14 | 2023 | 3 | |
| 15 | 2023 | 24 | |
| 16 | 2023 | 2 | |
| 17 | 2023 | 13 | |
| 18 | 2022 | 13 | |
| 19 | 2021 | 16 | |
| 20 | 2019 | 73 |
About Cheng‐Lin Liu
Cheng‐Lin Liu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology, having authored 378 papers that have together received 12.7k indexed citations. Recurring topics across this work include Handwritten Text Recognition Techniques (187 papers), Image Retrieval and Classification Techniques (94 papers), Image Processing and 3D Reconstruction (62 papers), Advanced Image and Video Retrieval Techniques (58 papers), Natural Language Processing Techniques (48 papers), Text and Document Classification Technologies (43 papers), Domain Adaptation and Few-Shot Learning (38 papers) and Face and Expression Recognition (37 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (9.7k citations), Media Technology (2.3k citations) and Human-Computer Interaction (886 citations). Cheng‐Lin Liu has collaborated with scholars based in China, Japan and United Kingdom. Frequent co-authors include Fei Yin, Xu-Yao Zhang, Cordelia Schmid, Heng Wang, Alexander Kläser, Qiufeng Wang, Hiroshi Sako, Hiromichi Fujisawa, Da-Han Wang and Ching Y. Suen. Their work appears in journals such as Environmental Science & Technology, PLoS ONE and IEEE Transactions on Pattern Analysis and Machine 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.