Paul Sturgess
- Computer Vision and Pattern Recognition top 2%
- Aerospace Engineering top 10%
- Artificial Intelligence
- Environmental Engineering
- Automotive Engineering
- Co-authors
- Ľubor LadickýPhilip H. S. TorrSunando SenguptaKarteek AlahariShuai ZhengChris RussellYalın BaştanlarWilliam F. Clocksin
- Topics
- Advanced Image and Video Retrieval Techniques (8 papers)Advanced Vision and Imaging (3 papers)Advanced Neural Network Applications (3 papers)
- Journals
- ACM Transactions on GraphicsInternational Journal of Computer VisionUniversity of Hertfordshire Research Archive (University of Hertfordshire)
- Partner nations
- United KingdomTürkiyeIndia
In The Last Decade
Paul Sturgess
11 papers receiving 467 citations
Peers
Comparison fields: 5 of 48
- Computer Vision and Pattern Recognition 430
- Aerospace Engineering 145
- Artificial Intelligence 51
- Environmental Engineering 50
- Automotive Engineering 42
Countries citing papers authored by Paul Sturgess
This map shows the geographic impact of Paul Sturgess'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 Paul Sturgess with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paul Sturgess more than expected).
Fields of papers citing papers by Paul Sturgess
This network shows the impact of papers produced by Paul Sturgess. 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 Paul Sturgess. The network helps show where Paul Sturgess may publish in the future.
Co-authorship network of co-authors of Paul Sturgess
This figure shows the co-authorship network connecting the top 25 collaborators of Paul Sturgess. A scholar is included among the top collaborators of Paul Sturgess 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 Paul Sturgess. Paul Sturgess is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 42 | |
| 2 | 45 | |
| 3 | 40 | |
| 4 | 19 | |
| 5 | 60 | |
| 6 | 9 | |
| 7 | 9 | |
| 8 | 8 | |
| 9 | 77 | |
| 10 | 32 | |
| 11 | 137 |
About Paul Sturgess
Paul Sturgess is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Ocean Engineering, having authored 11 papers that have together received 478 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (8 papers), Advanced Vision and Imaging (3 papers) and Advanced Neural Network Applications (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (430 citations), Aerospace Engineering (145 citations) and Geology (31 citations). Paul Sturgess has collaborated with scholars based in United Kingdom, Türkiye and India. Frequent co-authors include Ľubor Ladický, Philip H. S. Torr, Sunando Sengupta, Karteek Alahari, Philip H. S. Torr, Shuai Zheng, Chris Russell, Yalın Baştanlar, William F. Clocksin and Vibhav Vineet. Their work appears in journals such as ACM Transactions on Graphics, International Journal of Computer Vision and University of Hertfordshire Research Archive (University of Hertfordshire).
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.