James S. Goddard

81 total papers · 870 total citations
53 papers, 591 citations indexed

About

James S. Goddard is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Radiation. According to data from OpenAlex, James S. Goddard has authored 53 papers receiving a total of 591 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Computer Vision and Pattern Recognition, 21 papers in Radiology, Nuclear Medicine and Imaging and 14 papers in Radiation. Recurrent topics in James S. Goddard's work include Medical Imaging Techniques and Applications (21 papers), Advanced Vision and Imaging (11 papers) and Industrial Vision Systems and Defect Detection (11 papers). James S. Goddard is often cited by papers focused on Medical Imaging Techniques and Applications (21 papers), Advanced Vision and Imaging (11 papers) and Industrial Vision Systems and Defect Detection (11 papers). James S. Goddard collaborates with scholars based in United States, Australia and United Kingdom. James S. Goddard's co-authors include Hamed Sari‐Sarraf, Mongi A. Abidi, Mark F. Smith, A.G. Weisenberger, Shaun S. Gleason, Justin S. Baba, S. Majewski, Michael J. Paulus, Vladimir Popov and Thomas P. Karnowski and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Industry Applications and Journal of Nuclear Medicine.

In The Last Decade

James S. Goddard

50 papers receiving 542 citations

Author Peers

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

Author Last Decade Papers Cites
James S. Goddard 238 174 133 127 127 53 591
Subrahmanyam Gorthi 364 1.5× 29 0.2× 112 0.8× 143 1.1× 72 0.6× 35 658
P.-E. Danielsson 168 0.7× 30 0.2× 25 0.2× 61 0.5× 71 0.6× 34 651
Xuenan Cui 253 1.1× 35 0.2× 50 0.4× 28 0.2× 124 1.0× 38 529
Peter D. Burns 314 1.3× 77 0.4× 145 1.1× 129 1.0× 21 0.2× 56 619
Yudan Wang 128 0.5× 239 1.4× 8 0.1× 72 0.6× 35 0.3× 37 555
Jingru Yi 395 1.7× 26 0.1× 88 0.7× 156 1.2× 140 1.1× 25 636
Stefan Heist 518 2.2× 35 0.2× 56 0.4× 199 1.6× 22 0.2× 52 634
Min Yang 119 0.5× 26 0.1× 30 0.2× 49 0.4× 166 1.3× 51 536
John W. Coltman 219 0.9× 12 0.1× 159 1.2× 43 0.3× 64 0.5× 25 605
Murat Tahtalı 289 1.2× 11 0.1× 45 0.3× 89 0.7× 70 0.6× 90 658

Countries citing papers authored by James S. Goddard

Since Specialization
Citations

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

Fields of papers citing papers by James S. Goddard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by James S. Goddard. 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 James S. Goddard. The network helps show where James S. Goddard may publish in the future.

Co-authorship network of co-authors of James S. Goddard

This figure shows the co-authorship network connecting the top 25 collaborators of James S. Goddard. A scholar is included among the top collaborators of James S. Goddard 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 James S. Goddard. James S. Goddard 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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