Carlos Caetano
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 5%
- Computer Networks and Communications top 10%
- Biomedical Engineering
- Signal Processing
- Co-authors
- William Robson SchwartzSilvio Jamil F. GuimarãesArnaldo de Albuquerque AraújoSandra AvilaJessica SenaJefersson A. dos SantosFrançois BrémondGuillermo Cámara-Chávez
- Topics
- Advanced Image and Video Retrieval Techniques (6 papers)Human Pose and Action Recognition (6 papers)Anomaly Detection Techniques and Applications (5 papers)
- Cited by
- Computer Vision and Pattern RecognitionArtificial IntelligenceComputer Networks and Communications
- Journals
- NeurocomputingIEEE Transactions on Circuits and Systems for Video TechnologyScientific Data
- Partner nations
- BrazilFranceSouth Korea
In The Last Decade
Carlos Caetano
14 papers receiving 359 citations
Peers
Comparison fields: 5 of 53
- Computer Vision and Pattern Recognition 287
- Artificial Intelligence 213
- Computer Networks and Communications 104
- Biomedical Engineering 74
- Signal Processing 42
Countries citing papers authored by Carlos Caetano
This map shows the geographic impact of Carlos Caetano'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 Carlos Caetano with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Carlos Caetano more than expected).
Fields of papers citing papers by Carlos Caetano
This network shows the impact of papers produced by Carlos Caetano. 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 Carlos Caetano. The network helps show where Carlos Caetano may publish in the future.
Co-authorship network of co-authors of Carlos Caetano
This figure shows the co-authorship network connecting the top 25 collaborators of Carlos Caetano. A scholar is included among the top collaborators of Carlos Caetano 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 Carlos Caetano. Carlos Caetano is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 62 | |
| 5 | 10 | |
| 6 | 1 | |
| 7 | 4 | |
| 8 | 41 | |
| 9 | 14 | |
| 10 | 140 | |
| 11 | 41 | |
| 12 | 19 | |
| 13 | Pornography detection using BossaNova video descriptor | 20 |
| 14 | 12 | |
| 15 | 6 |
About Carlos Caetano
Carlos Caetano is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing, having authored 15 papers that have together received 374 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (6 papers), Human Pose and Action Recognition (6 papers) and Anomaly Detection Techniques and Applications (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (287 citations), Artificial Intelligence (213 citations) and Computer Networks and Communications (104 citations). Carlos Caetano has collaborated with scholars based in Brazil, France and South Korea. Frequent co-authors include William Robson Schwartz, Silvio Jamil F. Guimarães, Arnaldo de Albuquerque Araújo, Sandra Avila, Jessica Sena, Jefersson A. dos Santos, François Brémond, Guillermo Cámara-Chávez, Gabriel Resende Gonçalves and Fabrício Benevenuto. Their work appears in journals such as Neurocomputing, IEEE Transactions on Circuits and Systems for Video Technology and Scientific Data.
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.