Eduardo Romera
- Computer Vision and Pattern Recognition top 0.5%
- Aerospace Engineering top 5%
- Artificial Intelligence top 5%
- Automotive Engineering top 2%
- Media Technology top 2%
- Co-authors
- Luis M. BergasaRoberto ArroyoJosé M. AlvarezKailun YangKaiwei WangPablo F. AlcantarillaRafael BareaElena López
- Topics
- Advanced Neural Network Applications (14 papers)Robotics and Sensor-Based Localization (9 papers)Video Surveillance and Tracking Methods (8 papers)
- Partner nations
- SpainChinaUnited States
In The Last Decade
Eduardo Romera
27 papers receiving 2.0k citations
Hit Papers
Peers
Comparison fields: 5 of 111
- Computer Vision and Pattern Recognition 1.5k
- Aerospace Engineering 407
- Artificial Intelligence 394
- Automotive Engineering 376
- Media Technology 170
Countries citing papers authored by Eduardo Romera
This map shows the geographic impact of Eduardo Romera'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 Eduardo Romera with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eduardo Romera more than expected).
Fields of papers citing papers by Eduardo Romera
This network shows the impact of papers produced by Eduardo Romera. 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 Eduardo Romera. The network helps show where Eduardo Romera may publish in the future.
Co-authorship network of co-authors of Eduardo Romera
This figure shows the co-authorship network connecting the top 25 collaborators of Eduardo Romera. A scholar is included among the top collaborators of Eduardo Romera 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 Eduardo Romera. Eduardo Romera is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 86 | |
| 3 | 33 | |
| 4 | Bridging the Day and Night Domain Gap for Semantic Segmentation | 2 |
| 5 | 81 | |
| 6 | 8 | |
| 7 | 21 | |
| 8 | 31 | |
| 9 | 82 | |
| 10 | 14 | |
| 11 | 10 | |
| 12 | 4 | |
| 13 | 25 | |
| 14 | 22 | |
| 15 | ERFNet: Efficient Residual Factorized ConvNet for Real-Time Semantic Segmentationbreakdown → | 1050 |
| 16 | 17 | |
| 17 | 19 | |
| 18 | 139 | |
| 19 | 67 | |
| 20 | 65 |
About Eduardo Romera
Eduardo Romera is a scholar working on Computer Vision and Pattern Recognition, Automotive Engineering and Aerospace Engineering, having authored 27 papers that have together received 2.0k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (14 papers), Robotics and Sensor-Based Localization (9 papers) and Video Surveillance and Tracking Methods (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.5k citations), Automotive Engineering (376 citations) and Media Technology (170 citations). Eduardo Romera has collaborated with scholars based in Spain, China and United States. Frequent co-authors include Luis M. Bergasa, Roberto Arroyo, José M. Alvarez, Kailun Yang, Kaiwei Wang, Pablo F. Alcantarilla, Rafael Barea, Elena López, Xinxin Hu and Ruiqi Cheng. Their work appears in journals such as Sensors, IEEE Transactions on Intelligent Transportation Systems and Autonomous Robots.
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.