Mario Christoudias
- Computer Vision and Pattern Recognition top 5%
- Aerospace Engineering top 10%
- Artificial Intelligence
- Media Technology top 10%
- Geology
- Co-authors
- T. P. TrzcinskiVincent LepetitPascal FuaTrevor DarrellRaquel UrtasunStanley PetersRaquel FernándezMatthew Frampton
- Topics
- Advanced Image and Video Retrieval Techniques (5 papers)Robotics and Sensor-Based Localization (4 papers)Image Retrieval and Classification Techniques (4 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceInfoscience (Ecole Polytechnique Fédérale de Lausanne)UvA-DARE (University of Amsterdam)
- Partner nations
- SwitzerlandAustriaUnited States
In The Last Decade
Mario Christoudias
5 papers receiving 285 citations
Peers
Comparison fields: 5 of 32
- Computer Vision and Pattern Recognition 260
- Aerospace Engineering 132
- Artificial Intelligence 52
- Media Technology 48
- Geology 12
Countries citing papers authored by Mario Christoudias
This map shows the geographic impact of Mario Christoudias'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 Mario Christoudias with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mario Christoudias more than expected).
Fields of papers citing papers by Mario Christoudias
This network shows the impact of papers produced by Mario Christoudias. 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 Mario Christoudias. The network helps show where Mario Christoudias may publish in the future.
Co-authorship network of co-authors of Mario Christoudias
This figure shows the co-authorship network connecting the top 25 collaborators of Mario Christoudias. A scholar is included among the top collaborators of Mario Christoudias 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 Mario Christoudias. Mario Christoudias is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 87 | |
| 2 | 116 | |
| 3 | Learning Image Descriptors with the Boosting-Trick | 54 |
| 4 | Boosting Binary Image Descriptors | 0 |
| 5 | 11 | |
| 6 | Bayesian Localized Multiple Kernel Learning | 24 |
About Mario Christoudias
Mario Christoudias is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Artificial Intelligence, having authored 6 papers that have together received 292 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (5 papers), Robotics and Sensor-Based Localization (4 papers) and Image Retrieval and Classification Techniques (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (260 citations), Media Technology (48 citations) and Aerospace Engineering (132 citations). Mario Christoudias has collaborated with scholars based in Switzerland, Austria and United States. Frequent co-authors include T. P. Trzcinski, Vincent Lepetit, Pascal Fua, Trevor Darrell, Raquel Urtasun, Stanley Peters, Raquel Fernández, Matthew Frampton and Patrick Ehlen. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Infoscience (Ecole Polytechnique Fédérale de Lausanne) and UvA-DARE (University of Amsterdam).
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.