Graham Leedham

79 total papers · 1.8k total citations
51 papers, 1.1k citations indexed

About

Graham Leedham is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Signal Processing. According to data from OpenAlex, Graham Leedham has authored 51 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Computer Vision and Pattern Recognition, 16 papers in Media Technology and 11 papers in Signal Processing. Recurrent topics in Graham Leedham's work include Handwritten Text Recognition Techniques (32 papers), Vehicle License Plate Recognition (14 papers) and Image Processing and 3D Reconstruction (11 papers). Graham Leedham is often cited by papers focused on Handwritten Text Recognition Techniques (32 papers), Vehicle License Plate Recognition (14 papers) and Image Processing and 3D Reconstruction (11 papers). Graham Leedham collaborates with scholars based in Singapore, Australia and United Kingdom. Graham Leedham's co-authors include Lingyu Wang, Vladimir Pervouchine, Lei Wang, Michael Blumenstein, Yan Chen, Vu Nguyen, Mian Li, Venu Govindaraju, S.D. Varma and Réjean Plamondon and has published in prestigious journals such as Pattern Recognition, Pattern Recognition Letters and Journal of Parallel and Distributed Computing.

In The Last Decade

Graham Leedham

45 papers receiving 1.0k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Graham Leedham 826 451 233 189 177 51 1.1k
Tieniu Tan 899 1.1× 405 0.9× 141 0.6× 184 1.0× 101 0.6× 31 1.2k
Jucheng Yang 407 0.5× 364 0.8× 94 0.4× 178 0.9× 185 1.0× 81 1.1k
Yingbo Zhou 555 0.7× 877 1.9× 62 0.3× 257 1.4× 239 1.4× 54 1.2k
Krešimir Delač 856 1.0× 477 1.1× 103 0.4× 202 1.1× 160 0.9× 27 1.2k
Tieniu Tan 884 1.1× 280 0.6× 97 0.4× 217 1.1× 126 0.7× 31 1.1k
Natalia A. Schmid 537 0.7× 647 1.4× 90 0.4× 69 0.4× 235 1.3× 71 916
Thirimachos Bourlai 756 0.9× 614 1.4× 97 0.4× 126 0.7× 182 1.0× 95 1.2k
Ajita Rattani 874 1.1× 871 1.9× 36 0.2× 111 0.6× 389 2.2× 89 1.3k
Marta Gomez‐Barrero 1.0k 1.2× 1.1k 2.5× 52 0.2× 215 1.1× 705 4.0× 55 1.5k
Lu Yang 489 0.6× 776 1.7× 48 0.2× 91 0.5× 120 0.7× 56 1.1k

Countries citing papers authored by Graham Leedham

Since Specialization
Citations

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

Fields of papers citing papers by Graham Leedham

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Graham Leedham

This figure shows the co-authorship network connecting the top 25 collaborators of Graham Leedham. A scholar is included among the top collaborators of Graham Leedham 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 Graham Leedham. Graham Leedham is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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