J. A. Becerra

109 total papers · 521 total citations
42 papers, 231 citations indexed

About

J. A. Becerra is a scholar working on Artificial Intelligence, Computer Networks and Communications and Computer Vision and Pattern Recognition. According to data from OpenAlex, J. A. Becerra has authored 42 papers receiving a total of 231 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Artificial Intelligence, 9 papers in Computer Networks and Communications and 8 papers in Computer Vision and Pattern Recognition. Recurrent topics in J. A. Becerra's work include Evolutionary Algorithms and Applications (12 papers), Reinforcement Learning in Robotics (11 papers) and Metaheuristic Optimization Algorithms Research (7 papers). J. A. Becerra is often cited by papers focused on Evolutionary Algorithms and Applications (12 papers), Reinforcement Learning in Robotics (11 papers) and Metaheuristic Optimization Algorithms Research (7 papers). J. A. Becerra collaborates with scholars based in Spain. J. A. Becerra's co-authors include Richard J. Duro, Francisco Bellas, Abraham Prieto, Fernando López Peña, José Sántos, Vicente Díaz Casás, Dora B. Heras, Francisco Argüello, José Reyes and Vicente García‐Díaz and has published in prestigious journals such as Sensors, Information Sciences and Neurocomputing.

In The Last Decade

J. A. Becerra

36 papers receiving 215 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
J. A. Becerra	126	47	33	30	25	42	231
Wojciech Turek	75 0.6×	51 1.1×	20 0.6×	86 2.9×	37 1.5×	51	224
Zhenping Xie	132 1.0×	68 1.4×	16 0.5×	31 1.0×	33 1.3×	50	280
Mariusz Flasiński	147 1.2×	72 1.5×	38 1.2×	11 0.4×	19 0.8×	24	280
Zhixing Huang	129 1.0×	25 0.5×	27 0.8×	58 1.9×	25 1.0×	44	270
Guangping Zeng	103 0.8×	58 1.2×	14 0.4×	54 1.8×	21 0.8×	56	278
Rehab F. Abdel‐Kader	101 0.8×	77 1.6×	14 0.4×	34 1.1×	22 0.9×	32	296
Longquan Yong	150 1.2×	35 0.7×	100 3.0×	12 0.4×	25 1.0×	51	326
Marie Farrell	111 0.9×	21 0.4×	99 3.0×	39 1.3×	37 1.5×	25	251
Darío Maravall	79 0.6×	81 1.7×	26 0.8×	60 2.0×	50 2.0×	22	235
Kuihua Huang	118 0.9×	51 1.1×	14 0.4×	25 0.8×	23 0.9×	40	250

Countries citing papers authored by J. A. Becerra

Since Specialization

Citations

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

Fields of papers citing papers by J. A. Becerra

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of J. A. Becerra

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

All Works

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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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