Pablo Márquez-Neila
- Computer Vision and Pattern Recognition top 2%
- Radiology, Nuclear Medicine and Imaging top 10%
- Biomedical Engineering
- Artificial Intelligence top 10%
- Ocean Engineering top 10%
- Co-authors
- Pascal FuaLuis BaumelaLuis ÁlvarezMathieu SalzmannMateusz KozińskiAgata MosinskaBugra TekinRaphael Sznitman
- Topics
- Medical Image Segmentation Techniques (8 papers)Advanced Image and Video Retrieval Techniques (5 papers)Cell Image Analysis Techniques (5 papers)
- Journals
- The Astrophysical JournalIEEE Transactions on Pattern Analysis and Machine IntelligenceScientific Reports
- Partner nations
- SwitzerlandSpainDominican Republic
In The Last Decade
Pablo Márquez-Neila
28 papers receiving 882 citations
Peers
Comparison fields: 5 of 116
- Computer Vision and Pattern Recognition 449
- Radiology, Nuclear Medicine and Imaging 163
- Biomedical Engineering 158
- Artificial Intelligence 127
- Ocean Engineering 85
Countries citing papers authored by Pablo Márquez-Neila
This map shows the geographic impact of Pablo Márquez-Neila'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 Pablo Márquez-Neila with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pablo Márquez-Neila more than expected).
Fields of papers citing papers by Pablo Márquez-Neila
This network shows the impact of papers produced by Pablo Márquez-Neila. 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 Pablo Márquez-Neila. The network helps show where Pablo Márquez-Neila may publish in the future.
Co-authorship network of co-authors of Pablo Márquez-Neila
This figure shows the co-authorship network connecting the top 25 collaborators of Pablo Márquez-Neila. A scholar is included among the top collaborators of Pablo Márquez-Neila 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 Pablo Márquez-Neila. Pablo Márquez-Neila 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 | 2 | |
| 3 | 3 | |
| 4 | 8 | |
| 5 | 2 | |
| 6 | 16 | |
| 7 | 4 | |
| 8 | 16 | |
| 9 | 15 | |
| 10 | 74 | |
| 11 | 5 | |
| 12 | 45 | |
| 13 | 5 | |
| 14 | 40 | |
| 15 | 147 | |
| 16 | Fusing 2D Uncertainty and 3D Cues for Monocular Body Pose Estimation. | 13 |
| 17 | 5 | |
| 18 | 18 | |
| 19 | 164 | |
| 20 | 40 |
About Pablo Márquez-Neila
Pablo Márquez-Neila is a scholar working on Biophysics, Computer Vision and Pattern Recognition and Structural Biology, having authored 28 papers that have together received 912 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (8 papers), Advanced Image and Video Retrieval Techniques (5 papers) and Cell Image Analysis Techniques (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (449 citations), Biophysics (64 citations) and Structural Biology (15 citations). Pablo Márquez-Neila has collaborated with scholars based in Switzerland, Spain and Dominican Republic. Frequent co-authors include Pascal Fua, Luis Baumela, Luis Álvarez, Mathieu Salzmann, Mateusz Koziński, Agata Mosinska, Bugra Tekin, Raphael Sznitman, Stéphane Cotin and Andrea Mendizábal. Their work appears in journals such as The Astrophysical Journal, IEEE Transactions on Pattern Analysis and Machine Intelligence and Scientific Reports.
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.