Javier de Lope
- Computer Vision and Pattern Recognition top 10%
- Artificial Intelligence top 10%
- Control and Systems Engineering top 10%
- Computer Networks and Communications top 10%
- Experimental and Cognitive Psychology
- Co-authors
- Darío MaravallManuel GrañaJosé Antonio Martín H.Matilde SantosJuan Pablo FuentesRichard J. DuroFélix de la Paz LópezPhilippe Corcia
- Topics
- Robotic Path Planning Algorithms (14 papers)Reinforcement Learning in Robotics (10 papers)Modular Robots and Swarm Intelligence (9 papers)
In The Last Decade
Javier de Lope
39 papers receiving 438 citations
Peers
Comparison fields: 5 of 103
- Computer Vision and Pattern Recognition 143
- Artificial Intelligence 139
- Control and Systems Engineering 89
- Computer Networks and Communications 81
- Experimental and Cognitive Psychology 57
Countries citing papers authored by Javier de Lope
This map shows the geographic impact of Javier de Lope'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 Javier de Lope with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Javier de Lope more than expected).
Fields of papers citing papers by Javier de Lope
This network shows the impact of papers produced by Javier de Lope. 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 Javier de Lope. The network helps show where Javier de Lope may publish in the future.
Co-authorship network of co-authors of Javier de Lope
This figure shows the co-authorship network connecting the top 25 collaborators of Javier de Lope. A scholar is included among the top collaborators of Javier de Lope 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 Javier de Lope. Javier de Lope is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 17 | |
| 3 | 7 | |
| 4 | 16 | |
| 5 | 13 | |
| 6 | 23 | |
| 7 | 3 | |
| 8 | Investigations into Lamarckism, Baldwinism and Local Search in Grammatical Evolution Guided by Reinforcement | 1 |
| 9 | 11 | |
| 10 | 9 | |
| 11 | 3 | |
| 12 | 0 | |
| 13 | 0 | |
| 14 | 3 | |
| 15 | 29 | |
| 16 | 24 | |
| 17 | 33 | |
| 18 | 13 | |
| 19 | 22 | |
| 20 | 0 |
About Javier de Lope
Javier de Lope is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Cultural Studies, having authored 43 papers that have together received 459 indexed citations. Recurring topics across this work include Robotic Path Planning Algorithms (14 papers), Reinforcement Learning in Robotics (10 papers) and Modular Robots and Swarm Intelligence (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (143 citations), Experimental and Cognitive Psychology (57 citations) and Artificial Intelligence (139 citations). Javier de Lope has collaborated with scholars based in Spain, Mexico and Chile. Frequent co-authors include Darío Maravall, Manuel Graña, José Antonio Martín H., Matilde Santos, Juan Pablo Fuentes, Richard J. Duro, Félix de la Paz López, Philippe Corcia, Hélène Blasco and Peter Bede. Their work appears in journals such as Information Sciences, Neurocomputing and Pattern Recognition Letters.
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.