Na Liu
- Electrical and Electronic Engineering top 10%
- Computer Networks and Communications top 2%
- Media Technology top 1%
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Topics
- Advanced Image Fusion Techniques (18 papers)Remote-Sensing Image Classification (16 papers)Image and Signal Denoising Methods (13 papers)
- Cited by
- Media TechnologyComputer Networks and CommunicationsComputer Vision and Pattern Recognition
- Journals
- SHILAP Revista de lepidopterologíaJournal of Hazardous MaterialsScientific Reports
- Partner nations
- ChinaUnited StatesFrance
In The Last Decade
Na Liu
58 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 103
- Electrical and Electronic Engineering 474
- Computer Networks and Communications 437
- Media Technology 345
- Computer Vision and Pattern Recognition 336
- Artificial Intelligence 100
Countries citing papers authored by Na Liu
This map shows the geographic impact of Na 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 Na Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Na Liu more than expected).
Fields of papers citing papers by Na Liu
This network shows the impact of papers produced by Na 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 Na Liu. The network helps show where Na Liu may publish in the future.
Co-authorship network of co-authors of Na Liu
This figure shows the co-authorship network connecting the top 25 collaborators of Na Liu. A scholar is included among the top collaborators of Na 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 Na Liu. Na 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 | 0 | |
| 2 | 2 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 16 | |
| 6 | 2 | |
| 7 | 32 | |
| 8 | 7 | |
| 9 | 50 | |
| 10 | 5 | |
| 11 | 1 | |
| 12 | 34 | |
| 13 | 23 | |
| 14 | 17 | |
| 15 | Network Slicing Based 5G and Future Mobile Networks: Mobility, Resource Management, and Challengesbreakdown → | 539 |
| 16 | 3 | |
| 17 | 4 | |
| 18 | 4 | |
| 19 | 2 | |
| 20 | 2 |
About Na Liu
Na Liu is a scholar working on Media Technology, Computer Vision and Pattern Recognition and Computational Mechanics, having authored 64 papers that have together received 1.2k indexed citations. Recurring topics across this work include Advanced Image Fusion Techniques (18 papers), Remote-Sensing Image Classification (16 papers) and Image and Signal Denoising Methods (13 papers). The work is most often cited by research in Media Technology (345 citations), Computer Networks and Communications (437 citations) and Computer Vision and Pattern Recognition (336 citations). Na Liu has collaborated with scholars based in China, United States and France. Frequent co-authors include Victor C. M. Leung, Haijun Zhang, Keping Long, A.H. Aghvami, Xiaoli Chu, Wei Li, Ran Tao, Qian Du, Huaihe Song and Xiaohong Chen. Their work appears in journals such as SHILAP Revista de lepidopterología, Journal of Hazardous Materials and Scientific Reports.
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.