Eric B. Lum

1.0k citations
33 papers · 710 · h-index 15

Impact in

Papers in

Eric B. Lum

33 papers receiving 668 citations

Peers

Eric B. Lum
Comparison fields: 5 of 73
  • Computer Graphics and Computer-Aided Design 547
  • Computer Vision and Pattern Recognition 549
  • Computational Mechanics 226
  • Signal Processing 41
  • Biophysics 18
Replace C. Correa with:
C. Correa United States
Simon Stegmaier Germany
Magnus Strengert Germany
Randi J. Rost United States
Will Usher United States
John Kessenich United States
José A. Iglesias-Guitián Italy
Mike Cammarano United States
Zoë J. Wood United States
Alexander Wiebel Germany
Eric B. Lum relative to C. Correa United States C. Correa's profile →
Citations per field
00.5×1.5×1.8×
C. Correa · 1×
Citations per year

Countries citing papers authored by Eric B. Lum

Since Specialization
Citations

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

Fields of papers citing papers by Eric B. Lum

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005105
2 200482
3 200261
4 200557
5 200454
6 201446
7 200243
8 200137
9 200228
10 200320
11 200320
12 200320
13 200219
14 200419
15 200617
16 201912
17
Feature-Enhanced Visualization of Multidimensional, Multivariate Volume Data Using Non-photorealistic Rendering Techniques
200212
18 200311
19 20029
20 20058

About Eric B. Lum

Eric B. Lum is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition, Computational Mechanics, Computer Networks and Communications and Artificial Intelligence, having authored 33 papers that have together received 710 indexed citations. Recurring topics across this work include Computer Graphics and Visualization Techniques (27 papers), 3D Shape Modeling and Analysis (15 papers), Advanced Vision and Imaging (11 papers), Data Visualization and Analytics (9 papers), Medical Image Segmentation Techniques (3 papers), Image Retrieval and Classification Techniques (3 papers), Computational Physics and Python Applications (2 papers) and Advanced Data Storage Technologies (2 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (547 citations), Computer Vision and Pattern Recognition (549 citations), Computational Mechanics (226 citations), Signal Processing (41 citations) and Biophysics (18 citations). Eric B. Lum has collaborated with scholars based in United States, Japan and United Kingdom. Frequent co-authors include Kwan‐Liu Ma, John Clyne, Shigeru Muraki, James Ahrens, John Patchett, Kwan-Liu Ma, James Shearer, Yi-Hsiang Hsu, Matthew J. Budoff and Larry D. Mesner. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, The Visual Computer, IEEE Sensors Journal, Microelectronic Engineering and IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control.

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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