João L. D. Comba

1.9k citations
96 papers · 1.3k indexed · h-index 21

João L. D. Comba

86 papers receiving 1.2k citations

Peers

João L. D. Comba
Comparison fields: 5 of 111
  • Computer Graphics and Computer-Aided Design 739
  • Computer Vision and Pattern Recognition 774
  • Computational Mechanics 476
  • Signal Processing 143
  • Acoustics and Ultrasonics 8
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Citations per field
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Citations per year

Countries citing papers authored by João L. D. Comba

Since Specialization
Citations

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

Fields of papers citing papers by João L. D. Comba

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by João L. D. Comba. 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 João L. D. Comba. The network helps show where João L. D. Comba may publish in the future.

Co-authorship network

The 25 scholars most cited alongside João L. D. Comba, 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 João L. D. Comba Line = papers co-authored together João L. D. Comba links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20240
3 20232
4 20232
5 20222
6 20217
7 20187
8 20170
9 20145
10 20136
11 201312
12 20123
13 200845
14 20089
15 200778
16
Volume Rendering of Time-Varying Scalar Fields on Unstructured Meshes
20060
17
A Survey of GPU-Based Volume Rendering of Unstructured Grids
200533
18
Explorando a Multidimensionalidade da Kd -Tree para Suporte a Temporalidade em Dados Espaciais Vetoriais do Tipo Ponto.
20031
19
Computation on GPUs: from a programmable pipeline to an efficient stream processor
20036
20 19999

About João L. D. Comba

João L. D. Comba is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Acoustics and Ultrasonics, having authored 96 papers that have together received 1.3k indexed citations. Recurring topics across this work include Computer Graphics and Visualization Techniques (49 papers), Data Visualization and Analytics (29 papers), 3D Shape Modeling and Analysis (28 papers), Computational Geometry and Mesh Generation (19 papers), Advanced Vision and Imaging (17 papers), Data Management and Algorithms (16 papers), Video Analysis and Summarization (5 papers) and Time Series Analysis and Forecasting (4 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (739 citations), Computer Vision and Pattern Recognition (774 citations) and Computational Mechanics (476 citations). João L. D. Comba has collaborated with scholars based in Brazil, United States and Netherlands. Frequent co-authors include Fábio Policarpo, Manuel M. Oliveira, Claudio Silva, Steven P. Callahan, Carlos Scheidegger, Rafael Torchelsen, Carla Maria Dal Sasso Freitas, Rui Bastos, Carlos A. Dietrich and M. Ikits. Their work appears in journals such as ACM Transactions on Graphics, Information Sciences and Applied Soft Computing.

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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