S.P. Luttrell
Impact in
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- Image and Signal Denoising Methods
- Face and Expression Recognition
- Advanced Data Compression Techniques
- Artificial Intelligence top 5%
- Neural Networks and Applications
- Advanced Clustering Algorithms Research
Papers in
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- Image and Signal Denoising Methods 12
- Advanced Data Compression Techniques 4
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- Neural Networks and Applications 10
- Target Tracking and Data Fusion in Sensor Networks 4
- Bayesian Methods and Mixture Models 4
- Co-authors
- C.J. Oliver (3 shared papers)B.R. Webber (1 shared paper)Sumio Wada (1 shared paper)L. M. Delves (2 shared papers)
- Journals
- Inverse Problems (6 papers)Nuclear Physics B (1 paper)Neural Computation (1 paper)Pattern Recognition Letters (1 paper)Journal of Physics D Applied Physics (1 paper)
- Partner nations
- United KingdomIndia
In The Last Decade
S.P. Luttrell
33 papers receiving 373 citations
Peers
Comparison fields: 5 of 70
- Computer Vision and Pattern Recognition 227
- Artificial Intelligence 295
- Signal Processing 66
- Media Technology 34
- Nuclear and High Energy Physics 29
Countries citing papers authored by S.P. Luttrell
This map shows the geographic impact of S.P. Luttrell'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 S.P. Luttrell with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S.P. Luttrell more than expected).
Fields of papers citing papers by S.P. Luttrell
This network shows the impact of papers produced by S.P. Luttrell. 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 S.P. Luttrell. The network helps show where S.P. Luttrell may publish in the future.
Co-authors
The 4 scholars most cited alongside S.P. Luttrell, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1994 | 72 | |
| 2 | 1990 | 68 | |
| 3 | 1989 | 41 | |
| 4 | 1985 | 36 | |
| 5 | 1991 | 35 | |
| 6 | 1989 | 31 | |
| 7 | 1981 | 31 | |
| 8 | 1989 | 23 | |
| 9 | 1985 | 17 | |
| 10 | 1986 | 17 | |
| 11 | 1988 | 13 | |
| 12 | 1990 | 12 | |
| 13 | 1985 | 11 | |
| 14 | Hierarchical self-organising networks | 1989 | 10 |
| 15 | 2005 | 10 | |
| 16 | 1992 | 10 | |
| 17 | 1994 | 10 | |
| 18 | Self-supervised training of hierarchical vector quantisers | 1991 | 6 |
| 19 | 1991 | 6 | |
| 20 | 1995 | 5 |
About S.P. Luttrell
S.P. Luttrell is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Aerospace Engineering, Signal Processing and Computational Mechanics, having authored 39 papers that have together received 497 indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (12 papers), Neural Networks and Applications (10 papers), Advanced SAR Imaging Techniques (6 papers), Sparse and Compressive Sensing Techniques (5 papers), Seismic Imaging and Inversion Techniques (4 papers), Advanced Data Compression Techniques (4 papers), Target Tracking and Data Fusion in Sensor Networks (4 papers) and Bayesian Methods and Mixture Models (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (227 citations), Artificial Intelligence (295 citations), Signal Processing (66 citations), Media Technology (34 citations) and Nuclear and High Energy Physics (29 citations). S.P. Luttrell has collaborated with scholars based in United Kingdom and India. Frequent co-authors include C.J. Oliver, B.R. Webber, Sumio Wada and L. M. Delves. Their work appears in journals such as Inverse Problems, Nuclear Physics B, Neural Computation, Pattern Recognition Letters and Journal of Physics D Applied Physics.
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.