D.L. Vilariño
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 5%
- Radiology, Nuclear Medicine and Imaging top 10%
- Computer Networks and Communications top 5%
- Electrical and Electronic Engineering
- Co-authors
- Francisco F. RiveraJosé C. CabaleiroTomás F. PenaJorge Martínez SánchezV.M. BreaD. CabelloPiotr DudekManuel G. Penedo
- Topics
- Neural Networks Stability and Synchronization (16 papers)Neural Networks and Applications (15 papers)Remote Sensing and LiDAR Applications (12 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE AccessComputer
In The Last Decade
D.L. Vilariño
56 papers receiving 1.6k citations
Hit Papers
Peers
Comparison fields: 5 of 168
- Artificial Intelligence 546
- Computer Vision and Pattern Recognition 283
- Radiology, Nuclear Medicine and Imaging 180
- Computer Networks and Communications 170
- Electrical and Electronic Engineering 163
Countries citing papers authored by D.L. Vilariño
This map shows the geographic impact of D.L. Vilariño'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 D.L. Vilariño with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites D.L. Vilariño more than expected).
Fields of papers citing papers by D.L. Vilariño
This network shows the impact of papers produced by D.L. Vilariño. 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 D.L. Vilariño. The network helps show where D.L. Vilariño may publish in the future.
Co-authorship network of co-authors of D.L. Vilariño
This figure shows the co-authorship network connecting the top 25 collaborators of D.L. Vilariño. A scholar is included among the top collaborators of D.L. Vilariño 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 D.L. Vilariño. D.L. Vilariño is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 4 | |
| 4 | 2 | |
| 5 | 14 | |
| 6 | 3 | |
| 7 | 20 | |
| 8 | 3 | |
| 9 | 0 | |
| 10 | 6 | |
| 11 | 2 | |
| 12 | Topographic cellular active contour techniques: theory, implementations and comparisons: Research Articles | 4 |
| 13 | 4 | |
| 14 | 8 | |
| 15 | 23 | |
| 16 | 19 | |
| 17 | A Target Identification Procedure for the Detection and Classification of Landmines from IR Images | 1 |
| 18 | 5 | |
| 19 | 3 | |
| 20 | 23 |
About D.L. Vilariño
D.L. Vilariño is a scholar working on Geology, Computer Vision and Pattern Recognition and Environmental Engineering, having authored 59 papers that have together received 1.6k indexed citations. Recurring topics across this work include Neural Networks Stability and Synchronization (16 papers), Neural Networks and Applications (15 papers) and Remote Sensing and LiDAR Applications (12 papers). The work is most often cited by research in Artificial Intelligence (546 citations), Computer Vision and Pattern Recognition (283 citations) and Ophthalmology (90 citations). D.L. Vilariño has collaborated with scholars based in Spain, Chile and Hungary. Frequent co-authors include Francisco F. Rivera, José C. Cabaleiro, Tomás F. Pena, Jorge Martínez Sánchez, V.M. Brea, D. Cabello, Piotr Dudek, Manuel G. Penedo, Csaba Rekeczky and A.J. Nieto. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Access and Computer.
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.