Adriana Dapena
- Signal Processing top 5%
- Electrical and Electronic Engineering
- Computer Networks and Communications top 10%
- Computer Vision and Pattern Recognition top 10%
- Artificial Intelligence
- Co-authors
- Paula M. CastroLuis CastedoCarlos J. EscuderoStanley C. AhaltM. González-LópezTiago M. Fernández‐CaramésAna Ares‐PernasJosé A. García‐Naya
- Topics
- Blind Source Separation Techniques (24 papers)Wireless Communication Networks Research (16 papers)Advanced Wireless Communication Techniques (15 papers)
- Cited by
- Signal ProcessingComputer Networks and CommunicationsComputer Vision and Pattern Recognition
- Journals
- SHILAP Revista de lepidopterologíaIEEE Transactions on Signal ProcessingSensors
- Partner nations
- SpainFranceUnited States
In The Last Decade
Adriana Dapena
57 papers receiving 352 citations
Peers
Comparison fields: 5 of 82
- Signal Processing 137
- Electrical and Electronic Engineering 105
- Computer Networks and Communications 90
- Computer Vision and Pattern Recognition 61
- Artificial Intelligence 42
Countries citing papers authored by Adriana Dapena
This map shows the geographic impact of Adriana Dapena'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 Adriana Dapena with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Adriana Dapena more than expected).
Fields of papers citing papers by Adriana Dapena
This network shows the impact of papers produced by Adriana Dapena. 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 Adriana Dapena. The network helps show where Adriana Dapena may publish in the future.
Co-authorship network of co-authors of Adriana Dapena
This figure shows the co-authorship network connecting the top 25 collaborators of Adriana Dapena. A scholar is included among the top collaborators of Adriana Dapena 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 Adriana Dapena. Adriana Dapena 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 | 0 | |
| 3 | 18 | |
| 4 | 3 | |
| 5 | 2 | |
| 6 | 3 | |
| 7 | 4 | |
| 8 | 6 | |
| 9 | 3 | |
| 10 | Improving performance of H.264/AVC transmissions over vehicular networks | 2 |
| 11 | 1 | |
| 12 | 0 | |
| 13 | 1 | |
| 14 | 1 | |
| 15 | 1 | |
| 16 | 1 | |
| 17 | 1 | |
| 18 | 5 | |
| 19 | 1 | |
| 20 | 1 |
About Adriana Dapena
Adriana Dapena is a scholar working on Signal Processing, Computer Networks and Communications and Analytical Chemistry, having authored 61 papers that have together received 369 indexed citations. Recurring topics across this work include Blind Source Separation Techniques (24 papers), Wireless Communication Networks Research (16 papers) and Advanced Wireless Communication Techniques (15 papers). The work is most often cited by research in Signal Processing (137 citations), Computer Networks and Communications (90 citations) and Computer Vision and Pattern Recognition (61 citations). Adriana Dapena has collaborated with scholars based in Spain, France and United States. Frequent co-authors include Paula M. Castro, Luis Castedo, Carlos J. Escudero, Stanley C. Ahalt, M. González-López, Tiago M. Fernández‐Caramés, Ana Ares‐Pernas, José A. García‐Naya, Manuel Suárez-Albela and Paula Fraga‐Lamas. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Signal Processing and Sensors.
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.