Inmaculada Ventura
- Computer Graphics and Computer-Aided Design top 5%
- Computer Vision and Pattern Recognition top 10%
- Computer Networks and Communications top 10%
- Signal Processing top 10%
- Aerospace Engineering
- Co-authors
- José Miguel Díaz-BáñezCarlos SearaSergio CabelloStefan LangermanAnı́bal OlleroIván MazaPablo Pérez-LanteroJosé J. Acevedo
- Topics
- Computational Geometry and Mesh Generation (19 papers)Data Management and Algorithms (8 papers)Optimization and Search Problems (4 papers)
- Cited by
- Computer Graphics and Computer-Aided DesignSignal ProcessingComputer Vision and Pattern Recognition
In The Last Decade
Inmaculada Ventura
24 papers receiving 229 citations
Peers
Comparison fields: 5 of 39
- Computer Graphics and Computer-Aided Design 84
- Computer Vision and Pattern Recognition 83
- Computer Networks and Communications 75
- Signal Processing 69
- Aerospace Engineering 57
Countries citing papers authored by Inmaculada Ventura
This map shows the geographic impact of Inmaculada Ventura'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 Inmaculada Ventura with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Inmaculada Ventura more than expected).
Fields of papers citing papers by Inmaculada Ventura
This network shows the impact of papers produced by Inmaculada Ventura. 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 Inmaculada Ventura. The network helps show where Inmaculada Ventura may publish in the future.
Co-authorship network of co-authors of Inmaculada Ventura
This figure shows the co-authorship network connecting the top 25 collaborators of Inmaculada Ventura. A scholar is included among the top collaborators of Inmaculada Ventura 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 Inmaculada Ventura. Inmaculada Ventura 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 | 3 | |
| 3 | 0 | |
| 4 | 3 | |
| 5 | 32 | |
| 6 | 2 | |
| 7 | 9 | |
| 8 | 5 | |
| 9 | 13 | |
| 10 | 12 | |
| 11 | 4 | |
| 12 | 3 | |
| 13 | 13 | |
| 14 | 2 | |
| 15 | 12 | |
| 16 | 3 | |
| 17 | 1 | |
| 18 | Reverse facility location problems | 37 |
| 19 | Covering Point Sets with Two Convex Objects | 2 |
| 20 | 5 |
About Inmaculada Ventura
Inmaculada Ventura is a scholar working on Computer Graphics and Computer-Aided Design, Signal Processing and Industrial and Manufacturing Engineering, having authored 26 papers that have together received 234 indexed citations. Recurring topics across this work include Computational Geometry and Mesh Generation (19 papers), Data Management and Algorithms (8 papers) and Optimization and Search Problems (4 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (84 citations), Signal Processing (69 citations) and Computer Vision and Pattern Recognition (83 citations). Inmaculada Ventura has collaborated with scholars based in Spain, Mexico and Chile. Frequent co-authors include José Miguel Díaz-Báñez, Carlos Seara, Sergio Cabello, Stefan Langerman, Anı́bal Ollero, Iván Maza, Pablo Pérez-Lantero, José J. Acevedo, Begoña C. Arrue and Jorge Urrutia. Their work appears in journals such as European Journal of Operational Research, Applied Mathematics and Computation and Annals of Operations Research.
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.