Francisco Chávez

815 total citations
44 papers, 397 citations indexed

About

Francisco Chávez is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Francisco Chávez has authored 44 papers receiving a total of 397 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 10 papers in Computer Vision and Pattern Recognition and 7 papers in Signal Processing. Recurrent topics in Francisco Chávez's work include Evolutionary Algorithms and Applications (8 papers), Metaheuristic Optimization Algorithms Research (5 papers) and Music Technology and Sound Studies (3 papers). Francisco Chávez is often cited by papers focused on Evolutionary Algorithms and Applications (8 papers), Metaheuristic Optimization Algorithms Research (5 papers) and Music Technology and Sound Studies (3 papers). Francisco Chávez collaborates with scholars based in Spain, Mexico and United States. Francisco Chávez's co-authors include Robert Pfeffer, Rajesh N. Davé, Pablo G. Debenedetti, Francisco J. Rodríguez, Pedro J. Pardo, Antonio Macı́as-Garcı́a, Gustavo Olague, Rafael Marcos Luque‐Baena, Rafael Alcalá and Francisco Fernández de Vega and has published in prestigious journals such as IEEE Access, Industrial & Engineering Chemistry Research and Colloids and Surfaces A Physicochemical and Engineering Aspects.

In The Last Decade

Francisco Chávez

44 papers receiving 379 citations

Peers

Francisco Chávez

Wenjie Yu China

Ge Song China

Zhiyan Liu China

Yuqian Zhang China

Palash Kumar Kundu India

Xiangyu Guo China

Xiaoyang Zheng China

P. Balamurugan India

Mihai Oltean Romania

Shouliang Li China

Wenjie Yu China

Francisco Chávez

62 ×0.6

28 ×0.4

12 ×0.2

50 ×1.0

22 ×0.5

Citations per year, relative to Francisco Chávez Francisco Chávez (= 1×) peers Wenjie Yu

Countries citing papers authored by Francisco Chávez

Since Specialization

Citations

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

Fields of papers citing papers by Francisco Chávez

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Francisco Chávez. 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 Francisco Chávez. The network helps show where Francisco Chávez may publish in the future.

Co-authorship network of co-authors of Francisco Chávez

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Gordo, J. Bussóns, et al.. (2023). Automatic Burst Detection in Solar Radio Spectrograms Using Deep Learning: deARCE Method. Solar Physics. 298(6). 4 indexed citations

Chávez, Francisco, et al.. (2023). Combining wavelet transform with convolutional neural networks for hypoglycemia events prediction from CGM data. Chemometrics and Intelligent Laboratory Systems. 243. 105017–105017. 5 indexed citations

Chávez, Francisco, et al.. (2021). Plum Ripeness Analysis in Real Environments Using Deep Learning with Convolutional Neural Networks. Agronomy. 11(11). 2353–2353. 13 indexed citations

Chávez, Francisco, et al.. (2021). Blood Glucose Prediction Using a Two Phase TSK Fuzzy Rule Based System. 2675. 712–719. 2 indexed citations

Vega, Francisco Fernández de, Gustavo Olague, Daniel Carlos Ferreira Lanza, et al.. (2020). Time and Individual Duration in Genetic Programming. IEEE Access. 8. 38692–38713. 9 indexed citations

Ortiz, Guadalupe, et al.. (2019). Real-Time Context-Aware Microservice Architecture for Predictive Analytics and Smart Decision-Making. IEEE Access. 7. 183177–183194. 23 indexed citations

Trujillo, Leonardo, et al.. (2019). Local search in speciation-based bloat control for genetic programming. Genetic Programming and Evolvable Machines. 20(3). 351–384. 10 indexed citations

Camacho, David, Raúl Lara-Cabrera, J. J. Merelo, et al.. (2018). From ephemeral computing to deep bioinspired algorithms: New trends and applications. Future Generation Computer Systems. 88. 735–746. 5 indexed citations

Vega, Francisco Fernández de, et al.. (2018). On the impact of STEM sustained actions on the future of young students. 136. 1–4. 2 indexed citations

10.

Díaz‐Álvarez, Josefa, et al.. (2018). A fuzzy rule-based system to predict energy consumption of genetic programming algorithms. Computer Science and Information Systems. 15(3). 635–654. 2 indexed citations

11.

Vega, Francisco Fernández de, et al.. (2017). Involving local administrations in STEM promotion: How to extend STEM initiatives to a whole region. 1. 1–7. 1 indexed citations

12.

Chávez, Francisco, et al.. (2017). GP-based motion control design for the double-integrator system subject to velocity constraint. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 73–74. 5 indexed citations

13.

Rodríguez, Francisco J., Antonio Macı́as-Garcı́a, Pedro J. Pardo, Francisco Chávez, & Rafael Marcos Luque‐Baena. (2017). Study and classification of plum varieties using image analysis and deep learning techniques. Progress in Artificial Intelligence. 7(2). 119–127. 43 indexed citations

14.

Chávez, Francisco, et al.. (2013). Self-adjusting focus of attention by means of GP for improving a laser point detection system. 1237–1244. 1 indexed citations

15.

Vega, Francisco Fernández de, et al.. (2013). Unplugging evolutionary algorithms: On the sources of novelty and creativity. 2856–2863. 4 indexed citations

16.

Fernández, F.V., Francisco Chávez, Rafael Alcalá, & Francisco Herrera. (2011). Musical genre classification by means of Fuzzy Rule-Based Systems: A preliminary approach. 1141. 2571–2577. 5 indexed citations

17.

Hidalgo, J. Ignacio, et al.. (2010). Parallel Architectures and Bioinspired Algorithms. Parallel Computing. 36(10-11). 553–554. 12 indexed citations

18.

Chávez, Francisco, et al.. (2009). Cooperative and decomposable approaches on royal road functions. 1875–1876. 1 indexed citations

19.

Chávez, Francisco, et al.. (2008). An independent and non-intrusive laser pointer environment control device system. 37–46. 6 indexed citations

20.

Dukhin, S.S., Chao Zhu, Rajesh N. Davé, et al.. (2003). Dynamic interfacial tension near critical point of a solvent–antisolvent mixture and laminar jet stabilization. Colloids and Surfaces A Physicochemical and Engineering Aspects. 229(1-3). 181–199. 44 indexed citations

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.

Explore authors with similar magnitude of impact