Wilson E. Marcílio-Jr
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition
- Environmental Engineering
- Signal Processing
- Mechanical Engineering
- Co-authors
- Danilo Medeiros ElerMarcelo Medeiros ElerFernando V. PaulovichRogério Eduardo GarciaWajdi AljedaaniRafael M. MartinsJosé F. RodriguesWallace Casaca
- Topics
- Data Visualization and Analytics (5 papers)Image Retrieval and Classification Techniques (5 papers)Computer Graphics and Visualization Techniques (2 papers)
- Journals
- Expert Systems with ApplicationsRemote SensingIEEE Transactions on Visualization and Computer Graphics
- Partner nations
- BrazilSwedenNetherlands
In The Last Decade
Wilson E. Marcílio-Jr
11 papers receiving 329 citations
Hit Papers
Peers
Comparison fields: 5 of 130
- Artificial Intelligence 110
- Computer Vision and Pattern Recognition 41
- Environmental Engineering 23
- Signal Processing 21
- Mechanical Engineering 21
Countries citing papers authored by Wilson E. Marcílio-Jr
This map shows the geographic impact of Wilson E. Marcílio-Jr'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 Wilson E. Marcílio-Jr with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wilson E. Marcílio-Jr more than expected).
Fields of papers citing papers by Wilson E. Marcílio-Jr
This network shows the impact of papers produced by Wilson E. Marcílio-Jr. 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 Wilson E. Marcílio-Jr. The network helps show where Wilson E. Marcílio-Jr may publish in the future.
Co-authorship network of co-authors of Wilson E. Marcílio-Jr
This figure shows the co-authorship network connecting the top 25 collaborators of Wilson E. Marcílio-Jr. A scholar is included among the top collaborators of Wilson E. Marcílio-Jr 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 Wilson E. Marcílio-Jr. Wilson E. Marcílio-Jr is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 8 | |
| 3 | 18 | |
| 4 | 0 | |
| 5 | 3 | |
| 6 | 26 | |
| 7 | 1 | |
| 8 | 3 | |
| 9 | From explanations to feature selection: assessing SHAP values as feature selection mechanismbreakdown → | 266 |
| 10 | 0 | |
| 11 | 6 | |
| 12 | 0 | |
| 13 | 1 | |
| 14 | 4 |
About Wilson E. Marcílio-Jr
Wilson E. Marcílio-Jr is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Human Factors and Ergonomics, having authored 14 papers that have together received 338 indexed citations. Recurring topics across this work include Data Visualization and Analytics (5 papers), Image Retrieval and Classification Techniques (5 papers) and Computer Graphics and Visualization Techniques (2 papers). The work is most often cited by research in Human Factors and Ergonomics (15 citations), Health Informatics (6 citations) and Health Information Management (18 citations). Wilson E. Marcílio-Jr has collaborated with scholars based in Brazil, Sweden and Netherlands. Frequent co-authors include Danilo Medeiros Eler, Marcelo Medeiros Eler, Fernando V. Paulovich, Rogério Eduardo Garcia, Wajdi Aljedaani, Rafael M. Martins, José F. Rodrigues, Wallace Casaca, Danillo Roberto Pereira and Bruno Brandoli Machado. Their work appears in journals such as Expert Systems with Applications, Remote Sensing 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.