John Rasure

628 total citations
15 papers, 360 citations indexed

About

John Rasure is a scholar working on Computer Networks and Communications, Computer Vision and Pattern Recognition and Information Systems and Management. According to data from OpenAlex, John Rasure has authored 15 papers receiving a total of 360 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Computer Networks and Communications, 5 papers in Computer Vision and Pattern Recognition and 4 papers in Information Systems and Management. Recurrent topics in John Rasure's work include Distributed and Parallel Computing Systems (5 papers), Parallel Computing and Optimization Techniques (4 papers) and Scientific Computing and Data Management (4 papers). John Rasure is often cited by papers focused on Distributed and Parallel Computing Systems (5 papers), Parallel Computing and Optimization Techniques (4 papers) and Scientific Computing and Data Management (4 papers). John Rasure collaborates with scholars based in United States, Brazil and Mexico. John Rasure's co-authors include Κωνσταντίνος Κωνσταντινίδης, Mark S. Young, Charles Hansen, Roberto Lotufo, Richard H. Griffey, Cranos Williams and Scott Wilson and has published in prestigious journals such as IEEE Transactions on Image Processing, IEEE Transactions on Signal Processing and International Journal of Imaging Systems and Technology.

In The Last Decade

John Rasure

13 papers receiving 301 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
John Rasure United States 7 138 69 68 47 45 15 360
Bruno Raffin France 11 248 1.8× 43 0.6× 64 0.9× 29 0.6× 12 0.3× 41 446
L.O. Hertzberger Netherlands 12 57 0.4× 85 1.2× 221 3.3× 53 1.1× 44 1.0× 94 512
Ken Martin United States 9 110 0.8× 17 0.2× 39 0.6× 28 0.6× 8 0.2× 17 265
E. Wes Bethel United States 15 208 1.5× 76 1.1× 177 2.6× 80 1.7× 13 0.3× 38 511
Luís Paulo Santos Portugal 10 189 1.4× 20 0.3× 26 0.4× 37 0.8× 19 0.4× 46 333
Lars Nyland United States 12 165 1.2× 78 1.1× 67 1.0× 27 0.6× 11 0.2× 26 332
Mark Lutz Germany 6 26 0.2× 37 0.5× 63 0.9× 101 2.1× 29 0.6× 13 350
Liquan Xiao China 11 43 0.3× 130 1.9× 209 3.1× 71 1.5× 75 1.7× 60 478
Ken Joy United States 12 266 1.9× 15 0.2× 51 0.8× 58 1.2× 5 0.1× 37 521

Countries citing papers authored by John Rasure

Since Specialization
Citations

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

Fields of papers citing papers by John Rasure

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of John Rasure

This figure shows the co-authorship network connecting the top 25 collaborators of John Rasure. A scholar is included among the top collaborators of John Rasure 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 John Rasure. John Rasure is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

15 of 15 papers shown
1.
Rasure, John, et al.. (2003). The state of the art of visual languages for visualization. 202–209. 1 indexed citations
2.
Rasure, John, et al.. (2002). A visual language for image processing. 86–91. 12 indexed citations
3.
Rasure, John, et al.. (2002). Teaching image processing with Khoros. 1. 506–510. 12 indexed citations
4.
Rasure, John, et al.. (2002). Clustering and classification of multispectral magnetic resonance images. 32–37. 1 indexed citations
5.
Κωνσταντινίδης, Κωνσταντίνος & John Rasure. (1994). The Khoros software development environment for image and signal processing. IEEE Transactions on Image Processing. 3(3). 243–252. 133 indexed citations
6.
Rasure, John, et al.. (1992). The state of the art of visual languages for visualization. IEEE Visualization. 202–209. 21 indexed citations
7.
Rasure, John & Mark S. Young. (1992). <title>Open environment for image processing and software development</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 1659. 300–310. 37 indexed citations
8.
Rasure, John & Mark S. Young. (1992). Data flow visual languages. IEEE Potentials. 11(2). 30–33. 6 indexed citations
9.
Rasure, John, et al.. (1991). A desing environment for multidimensional signal processing. 24(1). 18–33. 1 indexed citations
10.
Rasure, John, et al.. (1991). An integrated data flow visual language and software development environment. Journal of Visual Languages & Computing. 2(3). 217–246. 78 indexed citations
11.
Rasure, John, et al.. (1991). A VLSI for real-time linear operations and transforms. IEEE Transactions on Signal Processing. 39(8). 1914–1917. 2 indexed citations
12.
Rasure, John, et al.. (1991). Near ground level sensing for spatial analysis of vegetation. NASA STI Repository (National Aeronautics and Space Administration). 1 indexed citations
13.
Rasure, John, et al.. (1990). Visual language and software development environment for image processing. International Journal of Imaging Systems and Technology. 2(3). 183–199. 51 indexed citations
15.

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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