Guan Pang
- Ocean Engineering top 1%
- Computer Vision and Pattern Recognition top 2%
- Environmental Engineering top 2%
- Media Technology top 1%
- Ecology top 10%
- Co-authors
- Saikat BasuJing Huangİlke DemirKrzysztof KoperskiDevis TuiaRamesh RaskarUlrich NeumannManohar Paluri
- Topics
- 3D Surveying and Cultural Heritage (5 papers)Remote Sensing and LiDAR Applications (5 papers)Robotics and Sensor-Based Localization (5 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEICE Transactions on Information and SystemsarXiv (Cornell University)
- Partner nations
- United StatesIsraelNetherlands
In The Last Decade
Guan Pang
14 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 77
- Ocean Engineering 557
- Computer Vision and Pattern Recognition 512
- Environmental Engineering 502
- Media Technology 433
- Ecology 127
Countries citing papers authored by Guan Pang
This map shows the geographic impact of Guan Pang'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 Guan Pang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guan Pang more than expected).
Fields of papers citing papers by Guan Pang
This network shows the impact of papers produced by Guan Pang. 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 Guan Pang. The network helps show where Guan Pang may publish in the future.
Co-authorship network of co-authors of Guan Pang
This figure shows the co-authorship network connecting the top 25 collaborators of Guan Pang. A scholar is included among the top collaborators of Guan Pang 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 Guan Pang. Guan Pang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 21 | |
| 3 | 24 | |
| 4 | 1 | |
| 5 | 159 | |
| 6 | Self-Supervised Feature Learning for Semantic Segmentation of Overhead Imagery. | 29 |
| 7 | DeepGlobe 2018: A Challenge to Parse the Earth through Satellite Imagesbreakdown → | 759 |
| 8 | 46 | |
| 9 | 18 | |
| 10 | 2 | |
| 11 | 24 | |
| 12 | 29 | |
| 13 | 5 | |
| 14 | 1 |
About Guan Pang
Guan Pang is a scholar working on Geology, Computer Vision and Pattern Recognition and Environmental Engineering, having authored 14 papers that have together received 1.1k indexed citations. Recurring topics across this work include 3D Surveying and Cultural Heritage (5 papers), Remote Sensing and LiDAR Applications (5 papers) and Robotics and Sensor-Based Localization (5 papers). The work is most often cited by research in Media Technology (433 citations), Ocean Engineering (557 citations) and Environmental Engineering (502 citations). Guan Pang has collaborated with scholars based in United States, Israel and Netherlands. Frequent co-authors include Saikat Basu, Jing Huang, İlke Demir, Krzysztof Koperski, Devis Tuia, Ramesh Raskar, Ulrich Neumann, Manohar Paluri, Suriya Singh and C. V. Jawahar. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEICE Transactions on Information and Systems and arXiv (Cornell University).
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.