Erick Rodrí­guez-Esparza

515 total citations
20 papers, 350 citations indexed

About

Erick Rodrí­guez-Esparza is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Vision and Pattern Recognition. According to data from OpenAlex, Erick Rodrí­guez-Esparza has authored 20 papers receiving a total of 350 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 7 papers in Computational Theory and Mathematics and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in Erick Rodrí­guez-Esparza's work include Metaheuristic Optimization Algorithms Research (8 papers), Advanced Multi-Objective Optimization Algorithms (7 papers) and Evolutionary Algorithms and Applications (7 papers). Erick Rodrí­guez-Esparza is often cited by papers focused on Metaheuristic Optimization Algorithms Research (8 papers), Advanced Multi-Objective Optimization Algorithms (7 papers) and Evolutionary Algorithms and Applications (7 papers). Erick Rodrí­guez-Esparza collaborates with scholars based in Mexico, Spain and Egypt. Erick Rodrí­guez-Esparza's co-authors include Diego Oliva, Marco Pérez‐Cisneros, Laura A. Zanella-Calzada, Loke Kok Foong, Ali Asghar Heidari, Daniel Zaldívar, Aboul Ella Hassanien, Robert J. Zawadzki, Ratheesh K. Meleppat and Antonio D. Masegosa and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and Knowledge-Based Systems.

In The Last Decade

Erick Rodrí­guez-Esparza

16 papers receiving 341 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Erick Rodrí­guez-Esparza Mexico 7 131 131 78 49 46 20 350
Shankar Thawkar India 14 142 1.1× 228 1.7× 218 2.8× 78 1.6× 28 0.6× 23 511
Savita Ahlawat India 7 289 2.2× 111 0.8× 56 0.7× 23 0.5× 5 0.1× 19 466
Arunita Das India 11 148 1.1× 196 1.5× 25 0.3× 3 0.1× 46 1.0× 21 395
Muhammad Bilal Saudi Arabia 10 187 1.4× 52 0.4× 97 1.2× 41 0.8× 6 0.1× 44 411
Valentín Osuna-Enciso Mexico 11 204 1.6× 162 1.2× 24 0.3× 4 0.1× 64 1.4× 23 434
Jan M. Köhler Germany 2 167 1.3× 251 1.9× 134 1.7× 68 1.4× 8 0.2× 2 436
Mohammad Hashem Ryalat Jordan 10 80 0.6× 232 1.8× 79 1.0× 3 0.1× 60 1.3× 19 389
Rajesh Sharma R India 8 89 0.7× 57 0.4× 80 1.0× 27 0.6× 3 0.1× 42 274
Shenshen Gu China 9 81 0.6× 57 0.4× 14 0.2× 8 0.2× 10 0.2× 39 218
Md. Omaer Faruq Goni Bangladesh 13 173 1.3× 182 1.4× 312 4.0× 89 1.8× 2 0.0× 19 589

Countries citing papers authored by Erick Rodrí­guez-Esparza

Since Specialization
Citations

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

Fields of papers citing papers by Erick Rodrí­guez-Esparza

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Erick Rodrí­guez-Esparza. 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 Erick Rodrí­guez-Esparza. The network helps show where Erick Rodrí­guez-Esparza may publish in the future.

Co-authorship network of co-authors of Erick Rodrí­guez-Esparza

This figure shows the co-authorship network connecting the top 25 collaborators of Erick Rodrí­guez-Esparza. A scholar is included among the top collaborators of Erick Rodrí­guez-Esparza 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 Erick Rodrí­guez-Esparza. Erick Rodrí­guez-Esparza 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
1.
Rodrí­guez-Esparza, Erick, Antonio D. Masegosa, Diego Oliva, & Enrique Onieva. (2024). A new Hyper-heuristic based on Adaptive Simulated Annealing and Reinforcement Learning for the Capacitated Electric Vehicle Routing Problem. Expert Systems with Applications. 252. 124197–124197. 25 indexed citations
2.
3.
Morales-Castañeda, Bernardo, et al.. (2024). Adaptability and Efficiency in Population Management: A multi-population CMA-ES Strategy for High-Dimensional Optimization. Procedia Computer Science. 246. 1389–1398. 1 indexed citations
4.
Rodrí­guez-Esparza, Erick, et al.. (2024). Optimizing Road Traffic Surveillance: A Robust Hyper-Heuristic Approach for Vehicle Segmentation. IEEE Access. 12. 29503–29524. 5 indexed citations
5.
Rodrí­guez-Esparza, Erick, et al.. (2024). Handling the balance of operators in evolutionary algorithms through a weighted Hill Climbing approach. Knowledge-Based Systems. 294. 111784–111784. 1 indexed citations
6.
Valdivia, Arturo, et al.. (2024). IDEL: An Improved Differential Evolution with Lissajous Mutation. 1–8.
7.
8.
Rodrí­guez-Esparza, Erick, et al.. (2023). A two-phase metaheuristic approach for the parcel locker location problem: First select then merge. 9. 1–6. 1 indexed citations
9.
Morales-Castañeda, Bernardo, et al.. (2023). Improving the Convergence of the PSO Algorithm with a Stagnation Variable and Fuzzy Logic. 1–8. 2 indexed citations
10.
11.
Rodrí­guez-Esparza, Erick, et al.. (2023). LoLi-IEA: low-light image enhancement algorithm. 40–40. 2 indexed citations
12.
Rodrí­guez-Esparza, Erick, et al.. (2021). Inner limiting membrane segmentation and surface visualization method on retinal OCT images. 39–39. 1 indexed citations
13.
Rodrí­guez-Esparza, Erick, et al.. (2021). An efficient retinal blood vessel segmentation in eye fundus images by using optimized top-hat and homomorphic filtering. Computer Methods and Programs in Biomedicine. 201. 105949–105949. 68 indexed citations
14.
Rodrí­guez-Esparza, Erick, et al.. (2021). Classification of Apple Disease Based on Non-Linear Deep Features. Applied Sciences. 11(14). 6422–6422. 31 indexed citations
15.
Oliva, Diego, et al.. (2021). A selection hyperheuristic guided by Thompson sampling for numerical optimization. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 1394–1402. 2 indexed citations
16.
Rodrí­guez-Esparza, Erick, et al.. (2021). Identification of apple diseases in digital images by using the Gaining-sharing knowledge-based algorithm for multilevel thresholding. Soft Computing. 26(5). 2587–2623. 21 indexed citations
17.
Rodrí­guez-Esparza, Erick, Laura A. Zanella-Calzada, Diego Oliva, et al.. (2020). An efficient Harris hawks-inspired image segmentation method. Expert Systems with Applications. 155. 113428–113428. 164 indexed citations
18.
Oliva, Diego, Erick Rodrí­guez-Esparza, Mohamed Abd Elaziz, et al.. (2020). Balancing the Influence of Evolutionary Operators for Global optimization. 1–8. 10 indexed citations
19.
Rodrí­guez-Esparza, Erick, Laura A. Zanella-Calzada, Diego Oliva, & Marco Pérez‐Cisneros. (2020). Automatic detection and classification of abnormal tissues on digital mammograms based on a bag-of-visual-words approach. 73–73. 12 indexed citations
20.
Rodrí­guez-Esparza, Erick, Laura A. Zanella-Calzada, Diego Oliva, Salvador Hinojosa, & Marco Pérez‐Cisneros. (2019). Multilevel segmentation for automatic detection of malignant masses in digital mammograms based on threshold comparison. 4 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.

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