Maggie Wigness

59 total papers · 714 total citations
33 papers, 277 citations indexed

About

Maggie Wigness is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, Maggie Wigness has authored 33 papers receiving a total of 277 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Computer Vision and Pattern Recognition, 14 papers in Artificial Intelligence and 6 papers in Electrical and Electronic Engineering. Recurrent topics in Maggie Wigness's work include Advanced Image and Video Retrieval Techniques (6 papers), Visual Attention and Saliency Detection (5 papers) and Advanced Neural Network Applications (5 papers). Maggie Wigness is often cited by papers focused on Advanced Image and Video Retrieval Techniques (6 papers), Visual Attention and Saliency Detection (5 papers) and Advanced Neural Network Applications (5 papers). Maggie Wigness collaborates with scholars based in United States, China and Singapore. Maggie Wigness's co-authors include John G. Rogers, David K. Han, Sungmin Eum, Heesung Kwon, Bruce A. Draper, Luis E. Navarro‐Serment, Tarek Abdelzaher, J. Ross Beveridge, Shengzhong Liu and Philip David and has published in prestigious journals such as International Journal of Computer Vision, Real-Time Systems and Journal of Quantitative Analysis in Sports.

In The Last Decade

Maggie Wigness

29 papers receiving 275 citations

Author Peers

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

Author Last Decade Papers Cites
Maggie Wigness 183 83 68 35 30 33 277
Tin Lai 142 0.8× 70 0.8× 101 1.5× 24 0.7× 52 1.7× 26 293
Hui Zhang 187 1.0× 45 0.5× 52 0.8× 32 0.9× 30 1.0× 25 307
Jean-Charles Noyer 82 0.4× 78 0.9× 68 1.0× 36 1.0× 23 0.8× 28 217
Baifan Chen 166 0.9× 36 0.4× 93 1.4× 32 0.9× 37 1.2× 42 278
Christophe Debain 130 0.7× 38 0.5× 59 0.9× 35 1.0× 33 1.1× 22 270
Adarsh Jagan Sathyamoorthy 219 1.2× 72 0.9× 98 1.4× 46 1.3× 57 1.9× 17 318
Jinzhen Mu 186 1.0× 52 0.6× 121 1.8× 20 0.6× 29 1.0× 30 321
Tomasz Piotr Kucner 154 0.8× 69 0.8× 106 1.6× 98 2.8× 33 1.1× 34 295
Roland Schweiger 203 1.1× 80 1.0× 51 0.8× 132 3.8× 25 0.8× 29 306
Christophe Blanc 171 0.9× 88 1.1× 54 0.8× 83 2.4× 15 0.5× 19 286

Countries citing papers authored by Maggie Wigness

Since Specialization
Citations

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

Fields of papers citing papers by Maggie Wigness

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maggie Wigness

This figure shows the co-authorship network connecting the top 25 collaborators of Maggie Wigness. A scholar is included among the top collaborators of Maggie Wigness 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 Maggie Wigness. Maggie Wigness 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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