Felipe Codevilla
Impact in
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- Image Enhancement Techniques
- Advanced Neural Network Applications
- Advanced Image Processing Techniques
- Advanced Image and Video Retrieval Techniques
- Automotive Engineering top 10%
- Autonomous Vehicle Technology and Safety
Papers in
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- Image Enhancement Techniques 3
- Advanced Neural Network Applications 2
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- Autonomous Vehicle Technology and Safety 2
- Co-authors
- Antonio M. López (3 shared papers)Sílvia Silva da Costa Botelho (5 shared papers)Onay Urfalıoǧlu (1 shared paper)Amanda Duarte (1 shared paper)Paulo Drews (3 shared papers)Pedro L. Ballester (1 shared paper)Felix Heide (1 shared paper)Samira Ebrahimi Kahou (1 shared paper)
- Journals
- IEEE Transactions on Intelligent Transportation Systems (1 paper)IFAC-PapersOnLine (1 paper)OCEANS 2016 - Shanghai (1 paper)arXiv (Cornell University) (1 paper)2013 OCEANS - San Diego (1 paper)
In The Last Decade
Felipe Codevilla
8 papers receiving 360 citations
Peers
Comparison fields: 5 of 51
- Computer Vision and Pattern Recognition 231
- Automotive Engineering 94
- Media Technology 53
- Ocean Engineering 60
- Aerospace Engineering 86
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 10 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 | 186 | |
| 2 | 2016 | 86 | |
| 3 | 2015 | 45 | |
| 4 | 2015 | 29 | |
| 5 | 2014 | 15 | |
| 6 | 2023 | 7 | |
| 7 | 2013 | 2 | |
| 8 | Action-based Representation Learning for Autonomous Driving. | 2020 | 1 |
| 9 | 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, Media Technology and Aerospace Engineering, having authored 9 papers that have together received 371 indexed citations. Recurring topics across this work include Image Enhancement Techniques (3 papers), Robotics and Sensor-Based Localization (2 papers), Water Quality Monitoring Technologies (2 papers), Advanced Image Fusion Techniques (2 papers), Modular Robots and Swarm Intelligence (2 papers), Underwater Vehicles and Communication Systems (2 papers), Autonomous Vehicle Technology and Safety (2 papers) and Advanced Neural Network Applications (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (231 citations), Automotive Engineering (94 citations), Media Technology (53 citations), Ocean Engineering (60 citations) and Aerospace Engineering (86 citations). Felipe Codevilla has collaborated with scholars based in Brazil, Germany and Spain. Frequent co-authors include Antonio M. López, Sílvia Silva da Costa Botelho, Onay Urfalıoǧlu, Amanda Duarte, Paulo Drews, Pedro L. Ballester, Felix Heide, Samira Ebrahimi Kahou, Christopher Pal and Florian Golemo. Their work appears in journals such as IEEE Transactions on Intelligent Transportation Systems, IFAC-PapersOnLine, OCEANS 2016 - Shanghai, arXiv (Cornell University) and 2013 OCEANS - San Diego.
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.