Beatriz Pérez‐Sánchez

503 total citations
29 papers, 255 citations indexed

About

Beatriz Pérez‐Sánchez is a scholar working on Artificial Intelligence, Computer Networks and Communications and Information Systems. According to data from OpenAlex, Beatriz Pérez‐Sánchez has authored 29 papers receiving a total of 255 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 4 papers in Computer Networks and Communications and 3 papers in Information Systems. Recurrent topics in Beatriz Pérez‐Sánchez's work include Neural Networks and Applications (12 papers), Machine Learning and ELM (5 papers) and Data Stream Mining Techniques (5 papers). Beatriz Pérez‐Sánchez is often cited by papers focused on Neural Networks and Applications (12 papers), Machine Learning and ELM (5 papers) and Data Stream Mining Techniques (5 papers). Beatriz Pérez‐Sánchez collaborates with scholars based in Spain, Mexico and Canada. Beatriz Pérez‐Sánchez's co-authors include Óscar Fontenla-Romero, Bertha Guijarro‐Berdiñas, Amparo Alonso‐Betanzos, David Martínez‐Rego, Noelia Sánchez‐Maroño, José Luis Calvo‐Rolle, Carolina Bringas Molleda, Elena Hernández-Pereira, Francisco Javier Rodríguez‐Díaz and Diego Peteiro-Barral and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Pattern Recognition.

In The Last Decade

Beatriz Pérez‐Sánchez

27 papers receiving 246 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Beatriz Pérez‐Sánchez Spain 9 153 36 36 26 26 29 255
Hazem Migdady Jordan 10 93 0.6× 47 1.3× 54 1.5× 19 0.7× 24 0.9× 43 281
Mingfei Sun China 6 153 1.0× 26 0.7× 35 1.0× 47 1.8× 38 1.5× 15 305
Amanpreet Singh India 6 121 0.8× 20 0.6× 38 1.1× 44 1.7× 35 1.3× 19 306
Sandro Skansi Croatia 5 73 0.5× 20 0.6× 40 1.1× 31 1.2× 19 0.7× 14 244
Chenglong Wang China 10 59 0.4× 34 0.9× 60 1.7× 70 2.7× 35 1.3× 34 283
Jinhua Xu China 10 79 0.5× 68 1.9× 33 0.9× 64 2.5× 21 0.8× 40 240
Hugo Riggs United States 6 74 0.5× 62 1.7× 66 1.8× 9 0.3× 46 1.8× 16 238
Ankush Ghosh India 9 53 0.3× 22 0.6× 54 1.5× 41 1.6× 32 1.2× 47 258
Hoda El-Sayed United States 6 82 0.5× 12 0.3× 19 0.5× 24 0.9× 44 1.7× 17 228

Countries citing papers authored by Beatriz Pérez‐Sánchez

Since Specialization
Citations

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

Fields of papers citing papers by Beatriz Pérez‐Sánchez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Beatriz Pérez‐Sánchez. 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 Beatriz Pérez‐Sánchez. The network helps show where Beatriz Pérez‐Sánchez may publish in the future.

Co-authorship network of co-authors of Beatriz Pérez‐Sánchez

This figure shows the co-authorship network connecting the top 25 collaborators of Beatriz Pérez‐Sánchez. A scholar is included among the top collaborators of Beatriz Pérez‐Sánchez 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 Beatriz Pérez‐Sánchez. Beatriz Pérez‐Sánchez 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.
Pérez‐Sánchez, Beatriz & Noelia Sánchez‐Maroño. (2023). GENDER SENSITIVE CONTENT IN MACHINE LEARNING SUBJECTS. INTED proceedings. 1. 2382–2390. 1 indexed citations
2.
Fontenla-Romero, Óscar, Bertha Guijarro‐Berdiñas, Elena Hernández-Pereira, & Beatriz Pérez‐Sánchez. (2023). FedHEONN: Federated and homomorphically encrypted learning method for one-layer neural networks. Future Generation Computer Systems. 149. 200–211. 8 indexed citations
3.
Pérez‐Sánchez, Beatriz, et al.. (2020). La Responsabilidad Social en CEMEX. SHILAP Revista de lepidopterología. 14(4). 175–187. 4 indexed citations
4.
Sánchez‐Maroño, Noelia, Óscar Fontenla-Romero, & Beatriz Pérez‐Sánchez. (2019). Classification of Microarray Data. Methods in molecular biology. 1986. 185–205. 5 indexed citations
5.
Fontenla-Romero, Óscar, et al.. (2018). LANN-DSVD: A privacy-preserving distributed algorithm for machine learning.. The European Symposium on Artificial Neural Networks. 1 indexed citations
6.
Rodríguez‐Díaz, Francisco Javier, et al.. (2017). Validación del Cuestionario de Violencia entre Novios-Revisado (DVQ-R). SHILAP Revista de lepidopterología. 1 indexed citations
7.
Fontenla-Romero, Óscar, Beatriz Pérez‐Sánchez, & Bertha Guijarro‐Berdiñas. (2017). An incremental non-iterative learning method for one-layer feedforward neural networks. Applied Soft Computing. 70. 951–958. 4 indexed citations
8.
Fontenla-Romero, Óscar, et al.. (2016). A fast learning algorithm for high dimensional problems: an application to microarrays.. The European Symposium on Artificial Neural Networks. 1 indexed citations
9.
Pérez‐Sánchez, Beatriz, Óscar Fontenla-Romero, & Bertha Guijarro‐Berdiñas. (2016). A review of adaptive online learning for artificial neural networks. Artificial Intelligence Review. 49(2). 281–299. 61 indexed citations
10.
Pérez‐Sánchez, Beatriz, Óscar Fontenla-Romero, & Noelia Sánchez‐Maroño. (2015). Selecting target concept in one-class classification for handling class imbalance problem. 15. 1–8. 6 indexed citations
11.
Pérez‐Sánchez, Beatriz, Óscar Fontenla-Romero, & Bertha Guijarro‐Berdiñas. (2014). Self-adaptive Topology Neural Network for Online Incremental Learning. 94–101. 1 indexed citations
12.
Rodríguez‐Díaz, Francisco Javier, Carolina Bringas Molleda, Marí­a de la Villa Moral Jiménez, Beatriz Pérez‐Sánchez, & Anastasio Ovejero Bernal. (2013). Relationship between psychoactive substance use and family maltreatment: a prison population analysis. Consultation of the Doctoral Thesis Database (TESEO) (Ministerio de Educación, Cultura y Deporte). 3 indexed citations
13.
Pérez‐Sánchez, Beatriz, Óscar Fontenla-Romero, Bertha Guijarro‐Berdiñas, & David Martínez‐Rego. (2013). An online learning algorithm for adaptable topologies of neural networks. Expert Systems with Applications. 40(18). 7294–7304. 12 indexed citations
14.
Peteiro-Barral, Diego, Bertha Guijarro‐Berdiñas, & Beatriz Pérez‐Sánchez. (2012). Learning from heterogeneously distributed data sets using artificial neural networks and genetic algorithms. 1 indexed citations
15.
Peteiro-Barral, Diego, Bertha Guijarro‐Berdiñas, Beatriz Pérez‐Sánchez, & Óscar Fontenla-Romero. (2011). A distributed learning algorithm based on two-layer artificial neural networks and genetic algorithms.. The European Symposium on Artificial Neural Networks. 1 indexed citations
16.
Molleda, Carolina Bringas, et al.. (2010). Socialización e Historia Penitenciaria. Redalyc (Universidad Autónoma del Estado de México). Vol. 1(nº 1). 101–101. 7 indexed citations
17.
Pérez‐Sánchez, Beatriz, Óscar Fontenla-Romero, & Bertha Guijarro‐Berdiñas. (2010). An incremental learning method for neural networks in adaptive environments. 1–8. 9 indexed citations
18.
Fontenla-Romero, Óscar, Bertha Guijarro‐Berdiñas, Beatriz Pérez‐Sánchez, & Amparo Alonso‐Betanzos. (2009). A new convex objective function for the supervised learning of single-layer neural networks. Pattern Recognition. 43(5). 1984–1992. 28 indexed citations
19.
Guijarro‐Berdiñas, Bertha, Óscar Fontenla-Romero, Beatriz Pérez‐Sánchez, & Amparo Alonso‐Betanzos. (2008). A Regularized Learning Method for Neural Networks Based on Sensitivity Analysis. The European Symposium on Artificial Neural Networks. 2023. 289–294. 1 indexed citations
20.
Alonso‐Betanzos, Amparo, et al.. (2007). Classification of computer intrusions using functional networks. A comparative study.. The European Symposium on Artificial Neural Networks. 579–584. 13 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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