Juan M. Calderón

483 citations
40 papers · 257 indexed · h-index 8
Topics
Distributed Control Multi-Agent Systems (9 papers)Robotic Path Planning Algorithms (8 papers)Mobile Crowdsensing and Crowdsourcing (6 papers)
Journals
SHILAP Revista de lepidopterologíaApplied SciencesIEEE Robotics and Automation Letters

In The Last Decade

Juan M. Calderón

35 papers receiving 247 citations

Peers

Juan M. Calderón
Comparison fields: 5 of 66
  • Computer Networks and Communications 93
  • Computer Vision and Pattern Recognition 88
  • Aerospace Engineering 71
  • Control and Systems Engineering 67
  • Artificial Intelligence 49
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Citations per field
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Citations per year

Countries citing papers authored by Juan M. Calderón

Since Specialization
Citations

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

Fields of papers citing papers by Juan M. Calderón

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Juan M. Calderón. 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 Juan M. Calderón. The network helps show where Juan M. Calderón may publish in the future.

Co-authorship network of co-authors of Juan M. Calderón

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 3
3 3
4 1
5 4
6 8
7 1
8 20
9 3
10 2
11 13
12 75
13 3
14 6
15
Fast path planning algorithm for the RoboCup small size league
0
16 13
17
Prácticas culturales y mediación social de la cultura artística
1
18 1
19
Estructura y función de la cadena productiva de carne de bovino en la ganadería ejidal de Tecpatán, Chiapas, México
3
20 5

About Juan M. Calderón

Juan M. Calderón is a scholar working on Computer Science Applications, Computer Vision and Pattern Recognition and Computer Networks and Communications, having authored 40 papers that have together received 257 indexed citations. Recurring topics across this work include Distributed Control Multi-Agent Systems (9 papers), Robotic Path Planning Algorithms (8 papers) and Mobile Crowdsensing and Crowdsourcing (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (88 citations), Computer Networks and Communications (93 citations) and Computer Science Applications (19 citations). Juan M. Calderón has collaborated with scholars based in United States, Colombia and El Salvador. Frequent co-authors include Gustavo A. Cardona, Luis G. Jaimes, Eduardo Mojica‐Nava, Wilfrido Moreno, Andrew Raij, Alfredo Weitzenfeld, Xiaohe Wu, Daniel Ruíz, Kostas Daniilidis and Néstor Peña. Their work appears in journals such as SHILAP Revista de lepidopterología, Applied Sciences and IEEE Robotics and Automation 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.

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