Tom E. Bishop

903 total citations
13 papers, 525 citations indexed

About

Tom E. Bishop is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Statistical and Nonlinear Physics. According to data from OpenAlex, Tom E. Bishop has authored 13 papers receiving a total of 525 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Computer Vision and Pattern Recognition, 5 papers in Media Technology and 1 paper in Statistical and Nonlinear Physics. Recurrent topics in Tom E. Bishop's work include Advanced Image Processing Techniques (8 papers), Advanced Vision and Imaging (5 papers) and Image Processing Techniques and Applications (5 papers). Tom E. Bishop is often cited by papers focused on Advanced Image Processing Techniques (8 papers), Advanced Vision and Imaging (5 papers) and Image Processing Techniques and Applications (5 papers). Tom E. Bishop collaborates with scholars based in United Kingdom, Spain and United States. Tom E. Bishop's co-authors include Paolo Favaro, Fred Nicolls, James R. Hopgood, Rafael Molina, Marcos V. Conde, Radu Timofte, Javier Mateos, Mohammad Tayeb Ghasr, Aggelos K. Katsaggelos and Antonio Grieco and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) and Proceedings - International Conference on Image Processing.

In The Last Decade

Tom E. Bishop

12 papers receiving 501 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Tom E. Bishop United Kingdom 7 467 243 50 45 23 13 525
Shuochen Su Canada 7 508 1.1× 235 1.0× 70 1.4× 29 0.6× 16 0.7× 9 613
Kshitij Marwah United States 4 208 0.4× 96 0.4× 61 1.2× 28 0.6× 14 0.6× 8 291
Haofeng Huang China 6 598 1.3× 247 1.0× 43 0.9× 31 0.7× 13 0.6× 12 656
Xiaoran Jiang France 9 362 0.8× 77 0.3× 24 0.5× 15 0.3× 28 1.2× 16 420
Gyeongmin Choe South Korea 10 513 1.1× 167 0.7× 31 0.6× 15 0.3× 7 0.3× 14 561
Ali Mosleh Canada 10 218 0.5× 99 0.4× 38 0.8× 15 0.3× 18 0.8× 15 283
Inchang Choi South Korea 8 448 1.0× 187 0.8× 101 2.0× 16 0.4× 9 0.4× 11 538
Changyin Zhou China 12 479 1.0× 455 1.9× 140 2.8× 94 2.1× 10 0.4× 22 647
Soheil Darabi United States 8 915 2.0× 186 0.8× 48 1.0× 34 0.8× 13 0.6× 11 984
Fahim Mannan United States 9 186 0.4× 81 0.3× 65 1.3× 30 0.7× 21 0.9× 16 346

Countries citing papers authored by Tom E. Bishop

Since Specialization
Citations

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

Fields of papers citing papers by Tom E. Bishop

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tom E. Bishop. 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 Tom E. Bishop. The network helps show where Tom E. Bishop may publish in the future.

Co-authorship network of co-authors of Tom E. Bishop

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

All Works

13 of 13 papers shown
1.
Conde, Marcos V., et al.. (2023). Efficient Multi-Lens Bokeh Effect Rendering and Transformation. 1633–1642. 6 indexed citations
2.
Laaksonen, Jorma, et al.. (2023). Learning by Hallucinating: Vision-Language Pre-training with Weak Supervision. 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 1073–1083. 2 indexed citations
3.
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5.
Bishop, Tom E., et al.. (2013). Multiview Active Shape Models with SIFT Descriptors for the 300-W Face Landmark Challenge. 378–385. 20 indexed citations
6.
Bishop, Tom E. & Paolo Favaro. (2011). The Light Field Camera: Extended Depth of Field, Aliasing, and Superresolution. IEEE Transactions on Pattern Analysis and Machine Intelligence. 34(5). 972–986. 254 indexed citations
7.
Bishop, Tom E., et al.. (2010). A Bayesian approach to shape from coded aperture. 27. 3521–3524. 3 indexed citations
8.
Mateos, Javier, Tom E. Bishop, Rafael Molina, & Aggelos K. Katsaggelos. (2009). Local Bayesian image restoration using variational methods and Gamma-Normal distributions. 48. 129–132. 1 indexed citations
9.
Bishop, Tom E. & Paolo Favaro. (2009). Plenoptic depth estimation from multiple aliased views. 1622–1629. 39 indexed citations
10.
Bishop, Tom E., et al.. (2009). Light field superresolution. 1–9. 141 indexed citations
11.
Bishop, Tom E., Rafael Molina, & James R. Hopgood. (2008). Blind restoration of blurred photographs via AR modelling and MCMC. 160. 669–672. 8 indexed citations
12.
Bishop, Tom E., Rafael Molina, & James R. Hopgood. (2007). Nonstationary Blind Image Restoration using Variational Methods. Proceedings - International Conference on Image Processing. I – 125. 5 indexed citations
13.
Bishop, Tom E. & James R. Hopgood. (2006). Blind Image Restoration Using a Block-Stationary Signal Model. 2. II–853. 5 indexed citations

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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