Scott A. King

74 papers receiving 1.4k citations

Peers

Scott A. King
Comparison fields: 5 of 153
  • Computer Graphics and Computer-Aided Design 73
  • Computer Vision and Pattern Recognition 226
  • Nature and Landscape Conservation 91
  • Biotechnology 50
  • Signal Processing 60
Replace Mingquan Zhou with:
Mingquan Zhou China
Richard L. Hoffman United States
David Rousseau France
Yeting Zhang China
Rainer Schubert Germany
Steven Mills New Zealand
A. Oosterlinck Belgium
Qian Qi China
Silvia Zuffi Italy
Jiro Tanaka Japan
Scott A. King relative to Mingquan Zhou China Mingquan Zhou's profile →
Citations per field
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Mingquan Zhou · 1×
Citations per year

Countries citing papers authored by Scott A. King

Since Specialization
Citations

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

Fields of papers citing papers by Scott A. King

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Scott A. King. 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 Scott A. King. The network helps show where Scott A. King may publish in the future.

Co-authors

The 25 scholars most cited alongside Scott A. King, 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 Scott A. King Line = papers co-authored together Scott A. King links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 78 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010166
2 2020133
3 1998101
4 199789
5 199856
6 202254
7 200250
8 201948
9 202246
10 200043
11 200743
12 200442
13 200538
14 200632
15 199630
16 202030
17 200329
18 202129
19 201928
20 201327

About Scott A. King

Scott A. King is a scholar working on Computer Vision and Pattern Recognition, Ecology, Global and Planetary Change, Artificial Intelligence and Environmental Engineering, having authored 78 papers that have together received 1.5k indexed citations. Recurring topics across this work include Coastal wetland ecosystem dynamics (7 papers), Human Motion and Animation (6 papers), Ecology and Vegetation Dynamics Studies (5 papers), 3D Shape Modeling and Analysis (5 papers), IoT and Edge/Fog Computing (4 papers), Cystic Fibrosis Research Advances (4 papers), Computer Graphics and Visualization Techniques (4 papers) and Robotic Path Planning Algorithms (4 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (73 citations), Computer Vision and Pattern Recognition (226 citations), Nature and Landscape Conservation (91 citations), Biotechnology (50 citations) and Signal Processing (60 citations). Scott A. King has collaborated with scholars based in United States, Australia and New Zealand. Frequent co-authors include Eric J. Sorscher, Richard E. Parent, Luis Rodolfo García Carrillo, Zsuzsa Bebők, Ning Zhang, Laha Ale, Timothy S. Mologne, Jeong S. Hong, Lucas S. McDonald and Anthony A. Romeo. Their work appears in journals such as Austral Ecology, ISPRS International Journal of Geo-Information, Journal of Biological Chemistry, Biochemistry and Remote Sensing.

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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