Songhua Liu
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Computer Graphics and Computer-Aided Design top 2%
- Cognitive Neuroscience
- Signal Processing
- Topics
- Generative Adversarial Networks and Image Synthesis (5 papers)Advanced Neural Network Applications (4 papers)Domain Adaptation and Few-Shot Learning (4 papers)
- Cited by
- Computer Graphics and Computer-Aided DesignComputer Vision and Pattern RecognitionArtificial Intelligence
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE AccessInternational Journal of Wireless and Mobile Computing
- Partner nations
- ChinaSingaporeNetherlands
In The Last Decade
Songhua Liu
18 papers receiving 427 citations
Hit Papers
Peers
Comparison fields: 5 of 58
- Computer Vision and Pattern Recognition 312
- Artificial Intelligence 119
- Computer Graphics and Computer-Aided Design 90
- Cognitive Neuroscience 40
- Signal Processing 31
Countries citing papers authored by Songhua Liu
This map shows the geographic impact of Songhua 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 Songhua Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Songhua Liu more than expected).
Fields of papers citing papers by Songhua Liu
This network shows the impact of papers produced by Songhua 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 Songhua Liu. The network helps show where Songhua Liu may publish in the future.
Co-authorship network of co-authors of Songhua Liu
This figure shows the co-authorship network connecting the top 25 collaborators of Songhua Liu. A scholar is included among the top collaborators of Songhua Liu 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 Songhua Liu. Songhua Liu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 9 | |
| 3 | 2 | |
| 4 | 57 | |
| 5 | 26 | |
| 6 | 6 | |
| 7 | 11 | |
| 8 | 2 | |
| 9 | 28 | |
| 10 | 51 | |
| 11 | AdaAttN: Revisit Attention Mechanism in Arbitrary Neural Style Transferbreakdown → | 212 |
| 12 | 3 | |
| 13 | 4 | |
| 14 | 5 | |
| 15 | 7 | |
| 16 | 6 | |
| 17 | 8 | |
| 18 | 1 |
About Songhua Liu
Songhua Liu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Graphics and Computer-Aided Design, having authored 18 papers that have together received 440 indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (5 papers), Advanced Neural Network Applications (4 papers) and Domain Adaptation and Few-Shot Learning (4 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (90 citations), Computer Vision and Pattern Recognition (312 citations) and Artificial Intelligence (119 citations). Songhua Liu has collaborated with scholars based in China, Singapore and Netherlands. Frequent co-authors include Xinchao Wang, Dongliang He, Fu Li, Tianwei Lin, Errui Ding, Zhengxing Sun, Meiling Wang, Xin Li, Qian Li and Ruonan Yu. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Access and International Journal of Wireless and Mobile 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.