Xosé M. Pardo
- Computer Vision and Pattern Recognition top 2%
- Cognitive Neuroscience top 10%
- Human-Computer Interaction top 5%
- Sensory Systems top 5%
- Aerospace Engineering
- Co-authors
- Xosé R. Fdez-VidalAntón García-DíazRaquel DosilVíctor LeboránCarlos V. RegueiroD. CabelloRoberto IglesiasRoberto Paredes
- Topics
- Medical Image Segmentation Techniques (9 papers)Robotics and Sensor-Based Localization (9 papers)Visual Attention and Saliency Detection (5 papers)
In The Last Decade
Xosé M. Pardo
36 papers receiving 652 citations
Peers
Comparison fields: 5 of 92
- Computer Vision and Pattern Recognition 503
- Cognitive Neuroscience 142
- Human-Computer Interaction 107
- Sensory Systems 99
- Aerospace Engineering 84
Countries citing papers authored by Xosé M. Pardo
This map shows the geographic impact of Xosé M. Pardo'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 Xosé M. Pardo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xosé M. Pardo more than expected).
Fields of papers citing papers by Xosé M. Pardo
This network shows the impact of papers produced by Xosé M. Pardo. 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 Xosé M. Pardo. The network helps show where Xosé M. Pardo may publish in the future.
Co-authorship network of co-authors of Xosé M. Pardo
This figure shows the co-authorship network connecting the top 25 collaborators of Xosé M. Pardo. A scholar is included among the top collaborators of Xosé M. Pardo 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 Xosé M. Pardo. Xosé M. Pardo 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 | 1 | |
| 3 | 6 | |
| 4 | 5 | |
| 5 | 3 | |
| 6 | 3 | |
| 7 | 62 | |
| 8 | 28 | |
| 9 | 97 | |
| 10 | 5 | |
| 11 | 8 | |
| 12 | 8 | |
| 13 | Scene recognition using visual attention, invariant local features and visual landmarks | 0 |
| 14 | 0 | |
| 15 | 12 | |
| 16 | 3 | |
| 17 | 5 | |
| 18 | 8 | |
| 19 | 2 | |
| 20 | 5 |
About Xosé M. Pardo
Xosé M. Pardo is a scholar working on Computer Vision and Pattern Recognition, Sensory Systems and Biophysics, having authored 38 papers that have together received 684 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (9 papers), Robotics and Sensor-Based Localization (9 papers) and Visual Attention and Saliency Detection (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (503 citations), Sensory Systems (99 citations) and Human-Computer Interaction (107 citations). Xosé M. Pardo has collaborated with scholars based in Spain, Portugal and Chile. Frequent co-authors include Xosé R. Fdez-Vidal, Antón García-Díaz, Raquel Dosil, Víctor Leborán, Carlos V. Regueiro, D. Cabello, Roberto Iglesias, Roberto Paredes, Jaime S. Cardoso and A. Mosquera. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Expert Systems with Applications and IEEE Transactions on Biomedical Engineering.
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.