Robert Gove

22 papers receiving 280 citations

Peers

Robert Gove
Comparison fields: 5 of 75
  • Computer Vision and Pattern Recognition 130
  • Signal Processing 46
  • Software 15
  • Statistical and Nonlinear Physics 43
  • Artificial Intelligence 87
Replace William H. Hsu with:
William H. Hsu United States
Ananth Kalyanaraman United States
Ioannis Karydis Greece
B. Johnson United Kingdom
Nathaniel Dean United States
Kaixiong Zhou United States
Kevin McDonald United Kingdom
Bruno Pinaud France
Ronald I. Greenberg United States
Qiuchi Li China
Robert Gove relative to William H. Hsu United States William H. Hsu's profile →
Citations per field
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Citations per year

Countries citing papers authored by Robert Gove

Since Specialization
Citations

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

Fields of papers citing papers by Robert Gove

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 23 scholars most cited alongside Robert Gove, 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 Robert Gove Line = papers co-authored together Robert Gove links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20221
2 202229
3 20214
4 20219
5 201911
6 20197
7 20195
8 201810
9 20167
10 201417
11 20149
12 20115
13 201125
14 201115
15 200924
16 200920
17 20031
18 19996
19 199911
20 199418

About Robert Gove

Robert Gove is a scholar working on Statistical and Nonlinear Physics, Software, Computer Vision and Pattern Recognition, Signal Processing and Hardware and Architecture, having authored 22 papers that have together received 306 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (10 papers), Data Visualization and Analytics (9 papers), Advanced Text Analysis Techniques (5 papers), Network Security and Intrusion Detection (3 papers), Plant and animal studies (3 papers), Advanced Malware Detection Techniques (3 papers), Software Engineering Research (2 papers) and Insect and Pesticide Research (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (130 citations), Signal Processing (46 citations), Software (15 citations), Statistical and Nonlinear Physics (43 citations) and Artificial Intelligence (87 citations). Robert Gove has collaborated with scholars based in United States, Sweden and Switzerland. Frequent co-authors include Cody Dunne, Ben Shneiderman, Judith L. Klavans, Bonnie J. Dorr, Olav Rueppell, Joshua Saxe, Nicholas Leiby, Keiji Kojima, Chris Basoglu and Giacomo Bergamo. Their work appears in journals such as International Journal of Imaging Systems and Technology, Journal of Systems Architecture, Computer Graphics Forum, IEEE Transactions on Consumer Electronics and IEEE Transactions on Visualization and Computer Graphics.

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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