Beatriz A. Garro

680 total citations
16 papers, 383 citations indexed

About

Beatriz A. Garro is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Beatriz A. Garro has authored 16 papers receiving a total of 383 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 3 papers in Molecular Biology. Recurrent topics in Beatriz A. Garro's work include Metaheuristic Optimization Algorithms Research (5 papers), Evolutionary Algorithms and Applications (5 papers) and Neural Networks and Applications (4 papers). Beatriz A. Garro is often cited by papers focused on Metaheuristic Optimization Algorithms Research (5 papers), Evolutionary Algorithms and Applications (5 papers) and Neural Networks and Applications (4 papers). Beatriz A. Garro collaborates with scholars based in Mexico, Bolivia and Argentina. Beatriz A. Garro's co-authors include Roberto A. Vázquez, Humberto Sossa and Katya Rodríguez‐Vázquez and has published in prestigious journals such as Applied Soft Computing, Computational Intelligence and Neuroscience and Cognitive Computation.

In The Last Decade

Beatriz A. Garro

15 papers receiving 364 citations

Peers

Beatriz A. Garro
Comparison fields: 5 of 78
  • Artificial Intelligence 218
  • Molecular Biology 75
  • Computer Vision and Pattern Recognition 73
  • Electrical and Electronic Engineering 54
  • Computer Networks and Communications 35
Replace Gourab Ghosh Roy with:
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Ibrahim Venkat Malaysia
Jiong Zhu China
Sandra Gómez-Canaval Spain
Hong-Mo Je South Korea
Shusen Zhou China
Zhiguo Yu China
Christian Moewes Germany
Chamara Kasun Liyanaarachchi Lekamalage Singapore
Gourab Ghosh Roy India View profile →
Citations per field, relative to Beatriz A. Garro
Beatriz A. Garro · 1×
Citations per year, relative to Beatriz A. Garro
Beatriz A. Garro · 1×

Countries citing papers authored by Beatriz A. Garro

Since Specialization
Citations

This map shows the geographic impact of Beatriz A. Garro'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 Beatriz A. Garro with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Beatriz A. Garro more than expected).

Fields of papers citing papers by Beatriz A. Garro

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Beatriz A. Garro. 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 Beatriz A. Garro. The network helps show where Beatriz A. Garro may publish in the future.

Co-authorship network of co-authors of Beatriz A. Garro

This figure shows the co-authorship network connecting the top 25 collaborators of Beatriz A. Garro. A scholar is included among the top collaborators of Beatriz A. Garro 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 Beatriz A. Garro. Beatriz A. Garro is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

16 of 16 papers shown
# Work Indexed citations
1 5
2 7
3 5
4 0
5 130
6 20
7 80
8 2
9
Back-Propagation vs Particle Swarm Optimization Algorithm: which Algorithm is better to adjust the Synaptic Weights of a Feed-Forward ANN?
15
10 41
11 3
12 31
13 17
14 13
15
A New Bi-directional Associative Memory
1
16 13

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.

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