Daniel Zaldívar
- Artificial Intelligence top 1%
- Computer Vision and Pattern Recognition top 1%
- Computational Theory and Mathematics top 1%
- Electrical and Electronic Engineering
- Media Technology top 1%
- Co-authors
- Erik CuevasMarco Pérez‐CisnerosDiego OlivaMiguel CienfuegosBernardo Morales-CastañedaFernando FaustoAlma RodríguezGonzalo Pájares
- Topics
- Metaheuristic Optimization Algorithms Research (32 papers)Evolutionary Algorithms and Applications (21 papers)Image and Object Detection Techniques (14 papers)
In The Last Decade
Daniel Zaldívar
87 papers receiving 2.6k citations
Hit Papers
Peers
Comparison fields: 5 of 139
- Artificial Intelligence 1.3k
- Computer Vision and Pattern Recognition 961
- Computational Theory and Mathematics 543
- Electrical and Electronic Engineering 310
- Media Technology 300
Countries citing papers authored by Daniel Zaldívar
This map shows the geographic impact of Daniel Zaldívar'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 Daniel Zaldívar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Zaldívar more than expected).
Fields of papers citing papers by Daniel Zaldívar
This network shows the impact of papers produced by Daniel Zaldívar. 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 Daniel Zaldívar. The network helps show where Daniel Zaldívar may publish in the future.
Co-authorship network of co-authors of Daniel Zaldívar
This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Zaldívar. A scholar is included among the top collaborators of Daniel Zaldívar 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 Daniel Zaldívar. Daniel Zaldívar 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 | 0 | |
| 3 | 5 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 4 | |
| 7 | 1 | |
| 8 | 16 | |
| 9 | 0 | |
| 10 | 164 | |
| 11 | A better balance in metaheuristic algorithms: Does it exist?breakdown → | 283 |
| 12 | 22 | |
| 13 | 55 | |
| 14 | 16 | |
| 15 | A swarm optimization algorithm inspired in the behavior of the social-spiderbreakdown → | 408 |
| 16 | 21 | |
| 17 | 16 | |
| 18 | 14 | |
| 19 | OPPOSITION-BASED ELECTROMAGNETISM-LIKE FOR GLOBAL OPTIMIZATION | 7 |
| 20 | 7 |
About Daniel Zaldívar
Daniel Zaldívar is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Artificial Intelligence, having authored 96 papers that have together received 2.7k indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (32 papers), Evolutionary Algorithms and Applications (21 papers) and Image and Object Detection Techniques (14 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (961 citations), Artificial Intelligence (1.3k citations) and Media Technology (300 citations). Daniel Zaldívar has collaborated with scholars based in Mexico, Spain and Germany. Frequent co-authors include Erik Cuevas, Marco Pérez‐Cisneros, Diego Oliva, Miguel Cienfuegos, Bernardo Morales-Castañeda, Fernando Fausto, Alma Rodríguez, Gonzalo Pájares, Humberto Sossa and Raúl Rojas. Their work appears in journals such as Expert Systems with Applications, IEEE Access and Information Sciences.
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.