Jair Cervantes

3.6k total citations · 1 hit paper
48 papers, 2.3k citations indexed

About

Jair Cervantes is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Information Systems. According to data from OpenAlex, Jair Cervantes has authored 48 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Computer Vision and Pattern Recognition, 21 papers in Artificial Intelligence and 6 papers in Information Systems. Recurrent topics in Jair Cervantes's work include Face and Expression Recognition (12 papers), Imbalanced Data Classification Techniques (6 papers) and Text and Document Classification Technologies (6 papers). Jair Cervantes is often cited by papers focused on Face and Expression Recognition (12 papers), Imbalanced Data Classification Techniques (6 papers) and Text and Document Classification Technologies (6 papers). Jair Cervantes collaborates with scholars based in Mexico, United Kingdom and France. Jair Cervantes's co-authors include Farid García‐Lamont, Asdrúbal López‐Chau, Lisbeth Rodríguez-Mazahua, Xiaoou Li, Wen Yu, Kang Li, Giner Alor‐Hernández, José Luis Sánchez-Cervantes, Jorge Luis García-Alcaráz and Isaac Machorro-Cano and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Expert Systems with Applications.

In The Last Decade

Jair Cervantes

45 papers receiving 2.2k citations

Hit Papers

A comprehensive survey on... 2020 2026 2022 2024 2020 400 800 1.2k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. A comprehensive survey on support vector machine classification: Applications, challenges and trends
    2020 1.4k citations Jair Cervantes, Farid García‐Lamont et al. Neurocomputing profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jair Cervantes Mexico 15 688 458 210 200 174 48 2.3k
Asdrúbal López‐Chau Mexico 12 639 0.9× 374 0.8× 198 0.9× 176 0.9× 159 0.9× 61 2.1k
Farid García‐Lamont Mexico 11 546 0.8× 358 0.8× 193 0.9× 129 0.6× 164 0.9× 38 1.9k
Tareq Abed Mohammed Iraq 7 754 1.1× 708 1.5× 274 1.3× 175 0.9× 186 1.1× 18 2.7k
Eva Cernadas Spain 16 832 1.2× 333 0.7× 159 0.8× 181 0.9× 167 1.0× 59 2.7k
Saad Albawi Iraq 8 753 1.1× 727 1.6× 260 1.2× 151 0.8× 195 1.1× 16 2.7k
Manuel Fernández-Delgado Spain 21 915 1.3× 353 0.8× 282 1.3× 242 1.2× 307 1.8× 86 3.3k
Saad Al-Azawi Iraq 6 733 1.1× 736 1.6× 274 1.3× 148 0.7× 192 1.1× 16 2.6k
Ming Zong China 13 930 1.4× 694 1.5× 190 0.9× 205 1.0× 192 1.1× 24 2.3k
Fabrice Rossi France 17 685 1.0× 365 0.8× 218 1.0× 114 0.6× 132 0.8× 79 2.1k
Lisbeth Rodríguez-Mazahua Mexico 13 521 0.8× 239 0.5× 238 1.1× 247 1.2× 224 1.3× 48 2.1k

Countries citing papers authored by Jair Cervantes

Since Specialization
Citations

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

Fields of papers citing papers by Jair Cervantes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jair Cervantes

This figure shows the co-authorship network connecting the top 25 collaborators of Jair Cervantes. A scholar is included among the top collaborators of Jair Cervantes 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 Jair Cervantes. Jair Cervantes 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.
Cervantes, Jair, et al.. (2025). Real-Time Robbery Detection in Public Transport Using Audio Recordings and Deep Learning. SN Computer Science. 6(4).
2.
Cervantes, Jair, et al.. (2024). Reconocimiento de Emociones Mediante Región de Ojos Utilizando Características Texturales, lbp y hog. SHILAP Revista de lepidopterología. 28(79). 22–33. 1 indexed citations
3.
Cervantes, Jair, et al.. (2024). Use of Computer Vision Techniques for Recognition of Diseases and Pests in Tomato Plants. Computación y Sistemas. 28(2). 1 indexed citations
4.
Cano, A., et al.. (2024). Impact of Cu doping on morphology, structural and optical characteristics of SnO2 thin films prepared by spray pyrolysis. MRS Advances. 9(23). 1849–1853. 1 indexed citations
5.
Cervantes, Jair, et al.. (2023). Optimal segmentation of image datasets by genetic algorithms using color spaces. Expert Systems with Applications. 238. 121950–121950. 12 indexed citations
6.
7.
García‐Lamont, Farid, et al.. (2021). Systematic segmentation method based on PCA of image hue features for white blood cell counting. PLoS ONE. 16(12). e0261857–e0261857. 4 indexed citations
8.
Cervantes, Jair, Farid García‐Lamont, Lisbeth Rodríguez-Mazahua, & Asdrúbal López‐Chau. (2020). A comprehensive survey on support vector machine classification: Applications, challenges and trends. Neurocomputing. 408. 189–215. 1405 indexed citations breakdown →
9.
Rodríguez-Mazahua, Lisbeth, et al.. (2018). Analysis of Medical Opinions about the Nonrealization of Autopsies in a Mexican Hospital Using Association Rules and Bayesian Networks. Scientific Programming. 2018. 1–21. 2 indexed citations
10.
García‐Lamont, Farid, et al.. (2018). Segmentation of images by color features: A survey. Neurocomputing. 292. 1–27. 147 indexed citations
11.
López‐Chau, Asdrúbal, et al.. (2017). Detection of Compound Leaves for Plant Identification. IEEE Latin America Transactions. 15(11). 2185–2190. 8 indexed citations
12.
García‐Lamont, Farid, et al.. (2016). Fruit Classification by Extracting Color Chromaticity, Shape and Texture Features: Towards an Application for Supermarkets. IEEE Latin America Transactions. 14(7). 3434–3443. 27 indexed citations
13.
Cervantes, Jair, et al.. (2015). Data selection based on decision tree for SVM classification on large data sets. Applied Soft Computing. 37. 787–798. 65 indexed citations
14.
Cervantes, Jair, Xiaoou Li, & Wen Yu. (2014). Imbalanced data classification via support vector machines and genetic algorithms. Connection Science. 26(4). 335–348. 12 indexed citations
15.
Cervantes, Jair, Xiaoou Li, & Wen Yu. (2013). Using Genetic Algorithm to Improve Classification Accuracy on Imbalanced Data. 2659–2664. 16 indexed citations
16.
Li, Xiaoou, Jair Cervantes, & Wen Yu. (2012). Fast classification for large data sets via random selection clustering and Support Vector Machines. Intelligent Data Analysis. 16(6). 897–914. 10 indexed citations
17.
López‐Chau, Asdrúbal, et al.. (2012). Data Selection Using Decision Tree for SVM Classification. 742–749. 9 indexed citations
18.
Cervantes, Jair, Xiaoou Li, & Wen Yu. (2009). Splice site detection in DNA sequences using a fast classification algorithm. 13. 2683–2688. 3 indexed citations
19.
Cervantes, Jair, Xiaoou Li, & Wen Yu. (2008). Support Vector classification for large data sets by reducing training data with change of classes. 2609–2614. 8 indexed citations
20.
Li, Xiaoou, Jair Cervantes, & Wen Yu. (2007). Two-stage svm classification for large data sets via randomly reducing and recovering training data. 3633–3638. 10 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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