Greg Knowles

1.9k citations
32 papers · 1.3k · h-index 13

Impact in

Papers in

Greg Knowles

30 papers receiving 1.2k citations

Peers

Greg Knowles
Comparison fields: 5 of 95
  • Computer Vision and Pattern Recognition 753
  • Signal Processing 291
  • Media Technology 153
  • Mathematical Physics 148
  • Applied Mathematics 147
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G.G. Walter United States
S. D. Riemenschneider Canada
Simon Setzer Germany
Christophe Rabut France
Ishtiaq Rasool Khan Saudi Arabia
Danilo Costarellı Italy
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Citations per field
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Citations per year

Countries citing papers authored by Greg Knowles

Since Specialization
Citations

This map shows the geographic impact of Greg Knowles'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 Greg Knowles with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Greg Knowles more than expected).

Fields of papers citing papers by Greg Knowles

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Greg Knowles. 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 Greg Knowles. The network helps show where Greg Knowles may publish in the future.

Co-authors

The 9 scholars most cited alongside Greg Knowles, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Greg Knowles Line = papers co-authored together Greg Knowles links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1992486
2
Vector measures and control systems
1975161
3 1990136
4 1991105
5 1982101
6 199067
7 198456
8 198737
9 198430
10 197822
11 198117
12 198517
13 198012
14 197611
15 20069
16 19858
17 19798
18 19868
19 20047
20 20025

About Greg Knowles

Greg Knowles is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computational Mechanics, Computational Theory and Mathematics and Media Technology, having authored 32 papers that have together received 1.3k indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (7 papers), Advanced Data Compression Techniques (5 papers), Building Energy and Comfort Optimization (4 papers), Advanced Image Fusion Techniques (4 papers), Advanced Numerical Methods in Computational Mathematics (4 papers), Advanced Mathematical Modeling in Engineering (4 papers), Parallel Computing and Optimization Techniques (3 papers) and Logic, programming, and type systems (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (753 citations), Signal Processing (291 citations), Media Technology (153 citations), Mathematical Physics (148 citations) and Applied Mathematics (147 citations). Greg Knowles has collaborated with scholars based in United Kingdom, Australia and United States. Frequent co-authors include Igor Kluvánek, R. J. Duffin, J. M. Ball, Martin Donnelley, Paul Gardner-Stephen, Charles V. Coffman, Andrew Zisserman, A. Blake and Bernard D. Coleman. Their work appears in journals such as Solar Energy, SIAM Journal on Control and Optimization, Electronics Letters, Archive for Rational Mechanics and Analysis and Journal of Optimization Theory and Applications.

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.

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