Guoying Liu
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence
- Media Technology top 5%
- Mechanical Engineering
- Aerospace Engineering
- Topics
- Image Retrieval and Classification Techniques (16 papers)Remote Sensing and Land Use (11 papers)Remote-Sensing Image Classification (11 papers)
- Journals
- The Journal of Chemical PhysicsSHILAP Revista de lepidopterologíaPLoS ONE
- Partner nations
- ChinaCanadaUnited States
In The Last Decade
Guoying Liu
62 papers receiving 454 citations
Peers
Comparison fields: 5 of 93
- Computer Vision and Pattern Recognition 215
- Artificial Intelligence 90
- Media Technology 88
- Mechanical Engineering 50
- Aerospace Engineering 39
Countries citing papers authored by Guoying Liu
This map shows the geographic impact of Guoying 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 Guoying Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guoying Liu more than expected).
Fields of papers citing papers by Guoying Liu
This network shows the impact of papers produced by Guoying 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 Guoying Liu. The network helps show where Guoying Liu may publish in the future.
Co-authorship network of co-authors of Guoying Liu
This figure shows the co-authorship network connecting the top 25 collaborators of Guoying Liu. A scholar is included among the top collaborators of Guoying 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 Guoying Liu. Guoying 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 | 3 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 5 | |
| 7 | 2 | |
| 8 | 1 | |
| 9 | 8 | |
| 10 | 14 | |
| 11 | 28 | |
| 12 | 2 | |
| 13 | 4 | |
| 14 | 3 | |
| 15 | Color image segmentation algorithm based on multi-level region merging | 2 |
| 16 | Online Multiple Sample Video Target Tracking with Separation of Detection Recognition and Tracking | 2 |
| 17 | 0 | |
| 18 | 4 | |
| 19 | 21 | |
| 20 | Research of predicting methods for carbon flux based on support vector regression | 1 |
About Guoying Liu
Guoying Liu is a scholar working on Media Technology, Computer Vision and Pattern Recognition and Library and Information Sciences, having authored 70 papers that have together received 472 indexed citations. Recurring topics across this work include Image Retrieval and Classification Techniques (16 papers), Remote Sensing and Land Use (11 papers) and Remote-Sensing Image Classification (11 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (215 citations), Media Technology (88 citations) and Library and Information Sciences (7 citations). Guoying Liu has collaborated with scholars based in China, Canada and United States. Frequent co-authors include Aimin Wang, Yun Zhang, Yongge Liu, J. Jonás̆, Y. Li, Le Yang, Mengting Liu, Peng Jia, Yun Zhang and Yucheng Zhao. Their work appears in journals such as The Journal of Chemical Physics, SHILAP Revista de lepidopterología and PLoS ONE.
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.