Carlos Orrite
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence
- Biomedical Engineering
- Human-Computer Interaction top 10%
- Aerospace Engineering
- Co-authors
- Grégory RogezPhilip H. S. TorrSrikumar RamalingamCarlos MedranoElías HerreroDimitrios MakrisJ.J. GuerreroJesús Martínez del Rincón
- Topics
- Human Pose and Action Recognition (11 papers)Video Surveillance and Tracking Methods (11 papers)Advanced Vision and Imaging (4 papers)
- Partner nations
- SpainUnited KingdomChile
In The Last Decade
Carlos Orrite
24 papers receiving 288 citations
Peers
Comparison fields: 5 of 49
- Computer Vision and Pattern Recognition 251
- Artificial Intelligence 83
- Biomedical Engineering 63
- Human-Computer Interaction 33
- Aerospace Engineering 20
Countries citing papers authored by Carlos Orrite
This map shows the geographic impact of Carlos Orrite'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 Orrite with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Carlos Orrite more than expected).
Fields of papers citing papers by Carlos Orrite
This network shows the impact of papers produced by Carlos Orrite. 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 Orrite. The network helps show where Carlos Orrite may publish in the future.
Co-authorship network of co-authors of Carlos Orrite
This figure shows the co-authorship network connecting the top 25 collaborators of Carlos Orrite. A scholar is included among the top collaborators of Carlos Orrite 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 Orrite. Carlos Orrite is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 18 | |
| 2 | 12 | |
| 3 | 32 | |
| 4 | 6 | |
| 5 | 2 | |
| 6 | ViVoLab and CVLab - MediaEval 2014: Violent Scenes Detection Affect Task | 6 |
| 7 | 13 | |
| 8 | 8 | |
| 9 | 2 | |
| 10 | 1 | |
| 11 | 14 | |
| 12 | 7 | |
| 13 | 2 | |
| 14 | 5 | |
| 15 | 13 | |
| 16 | 14 | |
| 17 | 1 | |
| 18 | 24 | |
| 19 | 2 | |
| 20 | 2 |
About Carlos Orrite
Carlos Orrite is a scholar working on Computer Vision and Pattern Recognition, Instrumentation and Computer Graphics and Computer-Aided Design, having authored 24 papers that have together received 302 indexed citations. Recurring topics across this work include Human Pose and Action Recognition (11 papers), Video Surveillance and Tracking Methods (11 papers) and Advanced Vision and Imaging (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (251 citations), Human-Computer Interaction (33 citations) and Artificial Intelligence (83 citations). Carlos Orrite has collaborated with scholars based in Spain, United Kingdom and Chile. Frequent co-authors include Grégory Rogez, Philip H. S. Torr, Srikumar Ramalingam, Carlos Medrano, Elías Herrero, Dimitrios Makris, J.J. Guerrero, Jesús Martínez del Rincón, Michele Orini and Pablo Laguna. Their work appears in journals such as IEEE Transactions on Cybernetics, Neurocomputing and Pattern Recognition Letters.
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.