Guoji Zhang
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 5%
- Computational Theory and Mathematics top 5%
- Molecular Biology
- Statistical and Nonlinear Physics top 10%
- Co-authors
- Qing LiuCarlotta DomeniconiZhiwen YuGuoxian YuYazhou RenHuzefa RangwalaJane YouLiu Guo-sheng
- Topics
- Face and Expression Recognition (11 papers)Machine Learning in Bioinformatics (7 papers)Computational Drug Discovery Methods (6 papers)
- Cited by
- Computer Vision and Pattern RecognitionArtificial IntelligenceComputational Theory and Mathematics
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Guoji Zhang
48 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 94
- Computer Vision and Pattern Recognition 593
- Artificial Intelligence 443
- Computational Theory and Mathematics 185
- Molecular Biology 169
- Statistical and Nonlinear Physics 84
Countries citing papers authored by Guoji Zhang
This map shows the geographic impact of Guoji Zhang'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 Guoji Zhang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guoji Zhang more than expected).
Fields of papers citing papers by Guoji Zhang
This network shows the impact of papers produced by Guoji Zhang. 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 Guoji Zhang. The network helps show where Guoji Zhang may publish in the future.
Co-authorship network of co-authors of Guoji Zhang
This figure shows the co-authorship network connecting the top 25 collaborators of Guoji Zhang. A scholar is included among the top collaborators of Guoji Zhang 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 Guoji Zhang. Guoji Zhang 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 | 1 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 10 | |
| 6 | 10 | |
| 7 | 7 | |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 7 | |
| 11 | 14 | |
| 12 | Protein function prediction by integrating multiple kernels | 14 |
| 13 | 52 | |
| 14 | 25 | |
| 15 | 4 | |
| 16 | 1 | |
| 17 | Liu, Q.: A novel image encryption method based on total shuffling scheme. Opt. Commun. 284, 2775-2780 | 6 |
| 18 | Study for the Numerical Properties of the Higher-Order LOD-FDTD Methods | 1 |
| 19 | 5 | |
| 20 | Decision tree method based on KPCA and its application | 0 |
About Guoji Zhang
Guoji Zhang is a scholar working on Computer Vision and Pattern Recognition, Computational Theory and Mathematics and Artificial Intelligence, having authored 52 papers that have together received 1.1k indexed citations. Recurring topics across this work include Face and Expression Recognition (11 papers), Machine Learning in Bioinformatics (7 papers) and Computational Drug Discovery Methods (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (593 citations), Artificial Intelligence (443 citations) and Computational Theory and Mathematics (185 citations). Guoji Zhang has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Qing Liu, Carlotta Domeniconi, Zhiwen Yu, Guoxian Yu, Yazhou Ren, Huzefa Rangwala, Jane You, Liu Guo-sheng, Guosheng Liu and Fernando L. Teixeira. Their work appears in journals such as Environment International, Energy and Renewable Energy.
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.