John A. Gerth

838 citations
16 papers · 641 · h-index 10

Impact in

Papers in

John A. Gerth

16 papers receiving 593 citations

Peers

John A. Gerth
Comparison fields: 5 of 71
  • Computer Graphics and Computer-Aided Design 72
  • Signal Processing 159
  • Computer Vision and Pattern Recognition 258
  • Computer Networks and Communications 225
  • Information Systems 191
Replace Hsiang‐Yun Wu with:
Hsiang‐Yun Wu Japan
Lide Wu China
C.T. Silva United States
Michael Balzer Germany
Hsing-Kuo Pao Taiwan
Jan C. A. van der Lubbe Netherlands
Zhengquan Xu China
Soon Tee Teoh United States
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John A. Gerth relative to Hsiang‐Yun Wu Japan Hsiang‐Yun Wu's profile →
Citations per field
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Citations per year

Countries citing papers authored by John A. Gerth

Since Specialization
Citations

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

Fields of papers citing papers by John A. Gerth

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

16 of 16 papers shown
#Work
1 1991126
2 2015121
3 2010106
4 200858
5 200649
6 200049
7 201236
8 200834
9 201123
10 198418
11 19966
12 20185
13 20114
14 19953
15 19832
16 19831

About John A. Gerth

John A. Gerth is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications, Statistical and Nonlinear Physics and Information Systems and Management, having authored 16 papers that have together received 641 indexed citations. Recurring topics across this work include Data Visualization and Analytics (7 papers), Complex Network Analysis Techniques (3 papers), Advanced Database Systems and Queries (3 papers), Internet Traffic Analysis and Secure E-voting (2 papers), Advanced Software Engineering Methodologies (2 papers), Remote Sensing and LiDAR Applications (2 papers), Service-Oriented Architecture and Web Services (2 papers) and Human Motion and Animation (1 paper). The work is most often cited by research in Computer Graphics and Computer-Aided Design (72 citations), Signal Processing (159 citations), Computer Vision and Pattern Recognition (258 citations), Computer Networks and Communications (225 citations) and Information Systems (191 citations). John A. Gerth has collaborated with scholars based in United States. Frequent co-authors include Pat Hanrahan, Justin Talbot, Xiao Ling, Alan Norton, Greg Turk, John R. Goodall, Michael D. Iannacone, Erik M. Ferragut, Robert A. Bridges and Tyson Condie. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, The Visual Computer, Mathematics and visualization, ACM SIGGRAPH Computer Graphics and Japanese Journal of Statistics and Data Science.

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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