Deyang Liu
Impact in
-
- Advanced Vision and Imaging
- Advanced Image Processing Techniques
- Image Enhancement Techniques
- Image and Video Quality Assessment
- Media Technology top 2%
- Advanced Optical Imaging Technologies
- Advanced Image Fusion Techniques
- Image Processing Techniques and Applications
Papers in
-
- Advanced Vision and Imaging 35
- Advanced Image Processing Techniques 25
- Image Enhancement Techniques 16
- Image and Video Quality Assessment 15
-
- Advanced Image Fusion Techniques 8
- Co-authors
- Ping An (34 shared papers)Ran Ma (14 shared papers)Xinpeng Huang (11 shared papers)Liquan Shen (13 shared papers)Chao Yang (10 shared papers)Qiang Wu (4 shared papers)Yan Huang (5 shared papers)Yuming Fang (8 shared papers)
In The Last Decade
Deyang Liu
72 papers receiving 739 citations
Peers
Comparison fields: 5 of 81
- Computer Vision and Pattern Recognition 499
- Media Technology 146
- Signal Processing 84
- Computational Mathematics 4
- Instrumentation 20
Countries citing papers authored by Deyang Liu
This map shows the geographic impact of Deyang 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 Deyang Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Deyang Liu more than expected).
Fields of papers citing papers by Deyang Liu
This network shows the impact of papers produced by Deyang 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 Deyang Liu. The network helps show where Deyang Liu may publish in the future.
Co-authors
The 25 scholars most cited alongside Deyang 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
Showing the 20 most-cited of 86 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 76 | |
| 2 | 2019 | 53 | |
| 3 | 2020 | 43 | |
| 4 | 2020 | 42 | |
| 5 | 2020 | 34 | |
| 6 | 2023 | 34 | |
| 7 | 2022 | 31 | |
| 8 | 2022 | 30 | |
| 9 | 2024 | 26 | |
| 10 | 2016 | 25 | |
| 11 | 2020 | 25 | |
| 12 | 2024 | 21 | |
| 13 | 2022 | 20 | |
| 14 | 2020 | 19 | |
| 15 | 2015 | 18 | |
| 16 | 2019 | 18 | |
| 17 | 2018 | 16 | |
| 18 | 2023 | 15 | |
| 19 | 2020 | 14 | |
| 20 | 2024 | 13 |
About Deyang Liu
Deyang Liu is a scholar working on Computer Vision and Pattern Recognition, Media Technology, Signal Processing, Instrumentation and Industrial and Manufacturing Engineering, having authored 86 papers that have together received 783 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (35 papers), Advanced Image Processing Techniques (25 papers), Image Enhancement Techniques (16 papers), Image and Video Quality Assessment (15 papers), Video Coding and Compression Technologies (15 papers), Advanced Image Fusion Techniques (8 papers), Additive Manufacturing Materials and Processes (7 papers) and High Entropy Alloys Studies (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (499 citations), Media Technology (146 citations), Signal Processing (84 citations), Computational Mathematics (4 citations) and Instrumentation (20 citations). Deyang Liu has collaborated with scholars based in China, Australia and Singapore. Frequent co-authors include Ping An, Ran Ma, Xinpeng Huang, Liquan Shen, Chao Yang, Qiang Wu, Yan Huang, Yuming Fang, Yifan Zuo and Yilei Chen. Their work appears in journals such as Signal Processing Image Communication, IEEE Transactions on Multimedia, IEEE Transactions on Circuits and Systems for Video Technology, IEEE Transactions on Image Processing and IEEE Signal Processing Letters.
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.