Michael B. Dillencourt

57 papers receiving 842 citations

Peers

Michael B. Dillencourt
Comparison fields: 5 of 112
  • Computer Vision and Pattern Recognition 330
  • Computer Networks and Communications 251
  • Computer Graphics and Computer-Aided Design 243
  • Computational Theory and Mathematics 185
  • Signal Processing 87
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S. J. Hong United States
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Citations per field
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Citations per year

Countries citing papers authored by Michael B. Dillencourt

Since Specialization
Citations

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

Fields of papers citing papers by Michael B. Dillencourt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael B. Dillencourt. 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 Michael B. Dillencourt. The network helps show where Michael B. Dillencourt may publish in the future.

Co-authorship network of co-authors of Michael B. Dillencourt

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2
SHARED VARIABLE PROGRAMMING BEYOND SHARED MEMORY: Bridging Distributed Memory with Mobile Agents
2
3
Distributed Parallel Computing using Navigational Programming: Orchestrating Computations Around Data.
1
4
Mobile Agents - The Right Vehicle for Distributed Sequential Computing
2
5
Messengers: Distributed Programming Using Mobile Agents
8
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Distributed Sequential Numerical Computing Using Mobile Agents: Moving Code to Data
1
7 53
8 0
9 13
10 6
11 1
12
LOGO DETECTION IN DOCUMENT IMAGES
28
13 15
14 5
15
On the Maximum Number of Intersections of Two Polyhedra in 2 and 3 Dimensions.
1
16
Fast optimal parallel algorithms for maximal matching in sparse graphs
1
17 8
18 2
19 348
20 19

About Michael B. Dillencourt

Michael B. Dillencourt is a scholar working on Computer Graphics and Computer-Aided Design, Hardware and Architecture and Computational Mathematics, having authored 65 papers that have together received 921 indexed citations. Recurring topics across this work include Computational Geometry and Mesh Generation (16 papers), Distributed and Parallel Computing Systems (15 papers) and Optimization and Search Problems (13 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (243 citations), Computer Vision and Pattern Recognition (330 citations) and Computational Theory and Mathematics (185 citations). Michael B. Dillencourt has collaborated with scholars based in United States, Australia and India. Frequent co-authors include Hanan Samet, Markku Tamminen, Lubomir Bic, Katherine L. Morse, David M. Mount, Nathan S. Netanyahu, Daniel S. Hirschberg, David Eppstein, Warren D. Smith and Hairong Kuang. Their work appears in journals such as Journal of the ACM, Pattern Recognition Letters and PRESENCE Virtual and Augmented Reality.

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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