David Bonar

749 citations
16 papers · 636 · h-index 11

Impact in

Papers in

David Bonar

16 papers receiving 619 citations

Peers

David Bonar
Comparison fields: 5 of 83
  • Geophysics 314
  • Computer Vision and Pattern Recognition 211
  • Ocean Engineering 103
  • Radiology, Nuclear Medicine and Imaging 105
  • Computational Mathematics 2
Replace Cuiping Li with:
Cuiping Li China
Yu Geng China
Qing Wei China
Kyung‐Chan Kim South Korea
Krzysztof Boryczko Poland
Martin Gohlke Germany
José Luis Romero Austria
Shahid A. Haider Canada
Fengkai Zhang China
Bilal Malik United States
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Citations per field
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Citations per year

Countries citing papers authored by David Bonar

Since Specialization
Citations

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

Fields of papers citing papers by David Bonar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 24 scholars most cited alongside David Bonar, 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 David Bonar Line = papers co-authored together David Bonar links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 2012174
2 1994106
3 201273
4 201261
5 201449
6 201043
7 199342
8 201226
9 201324
10 201216
11 201411
12
Time-frequency analysis via deconvolution with sparsity constraints
20104
13 20113
14 20182
15
Non-Local Means Denoising of Seismic Data
20121
16 20121

About David Bonar

David Bonar is a scholar working on Geophysics, Computer Vision and Pattern Recognition, Molecular Biology, Organic Chemistry and Ocean Engineering, having authored 16 papers that have together received 636 indexed citations. Recurring topics across this work include Seismic Imaging and Inversion Techniques (7 papers), Seismic Waves and Analysis (5 papers), Glycosylation and Glycoproteins Research (4 papers), Image and Signal Denoising Methods (4 papers), Galectins and Cancer Biology (2 papers), Statistical and numerical algorithms (2 papers), Hydraulic Fracturing and Reservoir Analysis (2 papers) and Carbohydrate Chemistry and Synthesis (2 papers). The work is most often cited by research in Geophysics (314 citations), Computer Vision and Pattern Recognition (211 citations), Ocean Engineering (103 citations), Radiology, Nuclear Medicine and Imaging (105 citations) and Computational Mathematics (2 citations). David Bonar has collaborated with scholars based in Canada, Germany and United States. Frequent co-authors include Mauricio D. Sacchi, David A. Rottenberg, Stephen C. Strother, Ismael Vera Rodriguez, Franz‐Georg Hanisch, Xiaoliang Xu, Jeih‐San Liow, Horst Schroten, Kirt Schaper and Katharina Janek. Their work appears in journals such as Journal of Biological Chemistry, Journal of Computer Assisted Tomography, Geophysics, Molecular & Cellular Proteomics and Geophysical Prospecting.

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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