Felipe Codevilla
Impact in
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- Image Enhancement Techniques
- Advanced Neural Network Applications
- Advanced Image Processing Techniques
- Robotic Path Planning Algorithms
- Automotive Engineering top 5%
- Autonomous Vehicle Technology and Safety
Papers in
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- Image Enhancement Techniques 3
- Advanced Neural Network Applications 3
- Video Surveillance and Tracking Methods 2
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- Autonomous Vehicle Technology and Safety 3
- Co-authors
- Antonio M. López (4 shared papers)Sílvia Silva da Costa Botelho (6 shared papers)Onay Urfalıoǧlu (1 shared paper)Amanda Duarte (1 shared paper)Vladlen Koltun (1 shared paper)Alexey Dosovitskiy (1 shared paper)Paulo Drews (3 shared papers)Pedro L. Ballester (1 shared paper)
- Journals
- IEEE Transactions on Intelligent Transportation Systems (1 paper)Lecture notes in computer science (2 papers)IFAC-PapersOnLine (1 paper)OCEANS 2016 - Shanghai (1 paper)arXiv (Cornell University) (1 paper)
In The Last Decade
Felipe Codevilla
10 papers receiving 454 citations
Peers
Comparison fields: 5 of 55
- Computer Vision and Pattern Recognition 283
- Automotive Engineering 148
- Media Technology 61
- Ocean Engineering 65
- Aerospace Engineering 101
Countries citing papers authored by Felipe Codevilla
This map shows the geographic impact of Felipe Codevilla'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 Felipe Codevilla with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Felipe Codevilla more than expected).
Fields of papers citing papers by Felipe Codevilla
This network shows the impact of papers produced by Felipe Codevilla. 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 Felipe Codevilla. The network helps show where Felipe Codevilla may publish in the future.
Co-authors
The 17 scholars most cited alongside Felipe Codevilla, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 200 | |
| 2 | 2016 | 93 | |
| 3 | 2018 | 61 | |
| 4 | 2015 | 51 | |
| 5 | 2015 | 31 | |
| 6 | 2014 | 16 | |
| 7 | 2023 | 8 | |
| 8 | 2015 | 6 | |
| 9 | 2013 | 2 | |
| 10 | Action-based Representation Learning for Autonomous Driving. | 2020 | 1 |
| 11 | Latent Variable Nested Set Transformers & AutoBots. | 2021 | 0 |
About Felipe Codevilla
Felipe Codevilla is a scholar working on Computer Vision and Pattern Recognition, Automotive Engineering, Ocean Engineering, Artificial Intelligence and Media Technology, having authored 11 papers that have together received 469 indexed citations. Recurring topics across this work include Image Enhancement Techniques (3 papers), Autonomous Vehicle Technology and Safety (3 papers), Advanced Neural Network Applications (3 papers), Robotics and Sensor-Based Localization (2 papers), Underwater Vehicles and Communication Systems (2 papers), Anomaly Detection Techniques and Applications (2 papers), Water Quality Monitoring Technologies (2 papers) and Video Surveillance and Tracking Methods (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (283 citations), Automotive Engineering (148 citations), Media Technology (61 citations), Ocean Engineering (65 citations) and Aerospace Engineering (101 citations). Felipe Codevilla has collaborated with scholars based in Brazil, Spain and Germany. Frequent co-authors include Antonio M. López, Sílvia Silva da Costa Botelho, Onay Urfalıoǧlu, Amanda Duarte, Vladlen Koltun, Alexey Dosovitskiy, Paulo Drews, Pedro L. Ballester, ASM Shihavuddin and Nuno Gracias. Their work appears in journals such as IEEE Transactions on Intelligent Transportation Systems, Lecture notes in computer science, IFAC-PapersOnLine, OCEANS 2016 - Shanghai and arXiv (Cornell University).
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.