Jair Cervantes

34 papers and 1.6k indexed citations i.

About

Jair Cervantes is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology. According to data from OpenAlex, Jair Cervantes has authored 34 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computer Vision and Pattern Recognition, 13 papers in Artificial Intelligence and 5 papers in Media Technology. Recurrent topics in Jair Cervantes’s work include Imbalanced Data Classification Techniques (5 papers), Smart Agriculture and AI (4 papers) and Spectroscopy and Chemometric Analyses (4 papers). Jair Cervantes is often cited by papers focused on Imbalanced Data Classification Techniques (5 papers), Smart Agriculture and AI (4 papers) and Spectroscopy and Chemometric Analyses (4 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‐Alcaraz and Patricia Talamás‐Rohana and has published in prestigious journals such as PLoS ONE, Expert Systems with Applications and Neurocomputing.

In The Last Decade

Co-authorship network of co-authors of Jair Cervantes i

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.

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).

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

Rankless by CCL
2025