Mark J. L. Orr
- Artificial Intelligence top 10%
- Control and Systems Engineering top 10%
- Computer Vision and Pattern Recognition top 10%
- Computational Mechanics
- Computational Theory and Mathematics
- Co-authors
- John HallamAlan MurrayTom LeonardRobert B. FisherS. NinomiyaEmanuele TruccoAndrew Fitzgibbon
- Topics
- Neural Networks and Applications (4 papers)Advanced Vision and Imaging (3 papers)Robotics and Sensor-Based Localization (3 papers)
- Cited by
- Artificial IntelligenceControl and Systems EngineeringComputer Vision and Pattern Recognition
- Partner nations
- United KingdomJapanUnited States
In The Last Decade
Mark J. L. Orr
10 papers receiving 371 citations
Peers
Comparison fields: 5 of 92
- Artificial Intelligence 193
- Control and Systems Engineering 103
- Computer Vision and Pattern Recognition 80
- Computational Mechanics 33
- Computational Theory and Mathematics 32
Countries citing papers authored by Mark J. L. Orr
This map shows the geographic impact of Mark J. L. Orr'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 Mark J. L. Orr with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark J. L. Orr more than expected).
Fields of papers citing papers by Mark J. L. Orr
This network shows the impact of papers produced by Mark J. L. Orr. 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 Mark J. L. Orr. The network helps show where Mark J. L. Orr may publish in the future.
Co-authorship network of co-authors of Mark J. L. Orr
This figure shows the co-authorship network connecting the top 25 collaborators of Mark J. L. Orr. A scholar is included among the top collaborators of Mark J. L. Orr 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 Mark J. L. Orr. Mark J. L. Orr is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 32 | |
| 2 | 30 | |
| 3 | 15 | |
| 4 | Recent advances in radial basis function networks | 48 |
| 5 | 256 | |
| 6 | 2 | |
| 7 | 3 | |
| 8 | 4 | |
| 9 | Experiments with a network-based geometric reasoning engine | 1 |
| 10 | 5 |
About Mark J. L. Orr
Mark J. L. Orr is a scholar working on Computer Vision and Pattern Recognition, Geology and Artificial Intelligence, having authored 10 papers that have together received 396 indexed citations. Recurring topics across this work include Neural Networks and Applications (4 papers), Advanced Vision and Imaging (3 papers) and Robotics and Sensor-Based Localization (3 papers). The work is most often cited by research in Artificial Intelligence (193 citations), Control and Systems Engineering (103 citations) and Computer Vision and Pattern Recognition (80 citations). Mark J. L. Orr has collaborated with scholars based in United Kingdom, Japan and United States. Frequent co-authors include John Hallam, Alan Murray, Tom Leonard, Robert B. Fisher, S. Ninomiya, Emanuele Trucco and Andrew Fitzgibbon. Their work appears in journals such as The International Journal of Robotics Research, Neural Computation and Image and Vision Computing.
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.