Yulan Guo
- Computer Vision and Pattern Recognition top 0.1%
- Geology top 0.02%
- Computational Mechanics top 0.2%
- Aerospace Engineering top 0.2%
- Environmental Engineering top 0.2%
- Topics
- Advanced Vision and Imaging (44 papers)Robotics and Sensor-Based Localization (40 papers)3D Surveying and Cultural Heritage (35 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Geoscience and Remote SensingIEEE Transactions on Image Processing
- Partner nations
- ChinaAustraliaUnited Kingdom
In The Last Decade
Yulan Guo
159 papers receiving 9.4k citations
Hit Papers
Peers
Comparison fields: 5 of 168
- Computer Vision and Pattern Recognition 5.8k
- Geology 2.9k
- Computational Mechanics 2.7k
- Aerospace Engineering 2.4k
- Environmental Engineering 2.3k
Countries citing papers authored by Yulan Guo
This map shows the geographic impact of Yulan 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 Yulan Guo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yulan Guo more than expected).
Fields of papers citing papers by Yulan Guo
This network shows the impact of papers produced by Yulan 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 Yulan Guo. The network helps show where Yulan Guo may publish in the future.
Co-authorship network of co-authors of Yulan Guo
This figure shows the co-authorship network connecting the top 25 collaborators of Yulan Guo. A scholar is included among the top collaborators of Yulan 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 Yulan Guo. Yulan 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 | 5 | |
| 3 | 6 | |
| 4 | 8 | |
| 5 | 45 | |
| 6 | 12 | |
| 7 | 7 | |
| 8 | 8 | |
| 9 | 8 | |
| 10 | 96 | |
| 11 | 16 | |
| 12 | 16 | |
| 13 | RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Cloudsbreakdown → | 1288 |
| 14 | 102 | |
| 15 | 108 | |
| 16 | 92 | |
| 17 | 31 | |
| 18 | 12 | |
| 19 | 103 | |
| 20 | 22 |
About Yulan Guo
Yulan Guo is a scholar working on Geology, Computer Vision and Pattern Recognition and Computer Graphics and Computer-Aided Design, having authored 168 papers that have together received 9.6k indexed citations. Recurring topics across this work include Advanced Vision and Imaging (44 papers), Robotics and Sensor-Based Localization (40 papers) and 3D Surveying and Cultural Heritage (35 papers). The work is most often cited by research in Geology (2.9k citations), Computer Vision and Pattern Recognition (5.8k citations) and Environmental Engineering (2.3k citations). Yulan Guo has collaborated with scholars based in China, Australia and United Kingdom. Frequent co-authors include Qingyong Hu, Mohammed Bennamoun, Li Liu, Wei An, Hao Liu, Jianwei Wan, Hanyun Wang, Ferdous Sohel, Min Lu and Andrew Markham. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Geoscience and Remote Sensing 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.