Di Guo
- Control and Systems Engineering top 2%
- Biomedical Engineering top 5%
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 5%
- Cognitive Neuroscience top 5%
- Topics
- Robot Manipulation and Learning (18 papers)Tactile and Sensory Interactions (13 papers)Multimodal Machine Learning Applications (12 papers)
- Cited by
- Human-Computer InteractionControl and Systems EngineeringComputer Vision and Pattern Recognition
- Journals
- SHILAP Revista de lepidopterologíaIEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Image Processing
- Partner nations
- ChinaUnited KingdomUnited States
In The Last Decade
Di Guo
66 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 88
- Control and Systems Engineering 654
- Biomedical Engineering 529
- Computer Vision and Pattern Recognition 400
- Artificial Intelligence 349
- Cognitive Neuroscience 311
Countries citing papers authored by Di Guo
This map shows the geographic impact of Di Guo'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 Di Guo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Di Guo more than expected).
Fields of papers citing papers by Di Guo
This network shows the impact of papers produced by Di Guo. 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 Di Guo. The network helps show where Di Guo may publish in the future.
Co-authorship network of co-authors of Di Guo
This figure shows the co-authorship network connecting the top 25 collaborators of Di Guo. A scholar is included among the top collaborators of Di Guo 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 Di Guo. Di Guo 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 | 0 | |
| 3 | 0 | |
| 4 | 2 | |
| 5 | 3 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 6 | |
| 10 | 13 | |
| 11 | Embodied Semantic Scene Graph Generation | 4 |
| 12 | 2 | |
| 13 | 26 | |
| 14 | Unsupervised Representation Learning by Invariance Propagation | 4 |
| 15 | 21 | |
| 16 | 24 | |
| 17 | 33 | |
| 18 | 35 | |
| 19 | 53 | |
| 20 | 7 |
About Di Guo
Di Guo is a scholar working on Human-Computer Interaction, Computer Vision and Pattern Recognition and Cognitive Neuroscience, having authored 73 papers that have together received 1.4k indexed citations. Recurring topics across this work include Robot Manipulation and Learning (18 papers), Tactile and Sensory Interactions (13 papers) and Multimodal Machine Learning Applications (12 papers). The work is most often cited by research in Human-Computer Interaction (250 citations), Control and Systems Engineering (654 citations) and Computer Vision and Pattern Recognition (400 citations). Di Guo has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Fuchun Sun, Huaping Liu, Bin Fang, Tao Kong, Ning Xi, Jie Qin, Shidong Jia, Chao Yang, Xi‐Ming Sun and Wuqiang Yang. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Image Processing.
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.