Pablo Escandell-Montero

700 total citations
23 papers, 498 citations indexed

About

Pablo Escandell-Montero is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Pablo Escandell-Montero has authored 23 papers receiving a total of 498 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 7 papers in Computer Vision and Pattern Recognition and 3 papers in Molecular Biology. Recurrent topics in Pablo Escandell-Montero's work include Machine Learning and ELM (9 papers), Neural Networks and Applications (5 papers) and Face and Expression Recognition (4 papers). Pablo Escandell-Montero is often cited by papers focused on Machine Learning and ELM (9 papers), Neural Networks and Applications (5 papers) and Face and Expression Recognition (4 papers). Pablo Escandell-Montero collaborates with scholars based in Spain, Germany and Austria. Pablo Escandell-Montero's co-authors include José M. Martínez-Martínez, Juan Gómez‐Sanchís, Emilio Soria‐Olivas, José D. Martín‐Guerrero, Rafael Magdalena‐Benedito, D. Lorente, J. Blasco, Marcelino Martínez‐Sober, Sergio Cubero and Andrea Stopper and has published in prestigious journals such as Expert Systems with Applications, Journal of Food Engineering and Neurocomputing.

In The Last Decade

Pablo Escandell-Montero

23 papers receiving 480 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pablo Escandell-Montero Spain 9 194 111 67 62 61 23 498
José M. Martínez-Martínez Spain 10 191 1.0× 54 0.5× 65 1.0× 32 0.5× 62 1.0× 22 462
Rafael Gomes Mantovani Brazil 12 239 1.2× 62 0.6× 76 1.1× 30 0.5× 42 0.7× 34 594
Assif Assad India 11 303 1.6× 49 0.4× 85 1.3× 49 0.8× 42 0.7× 43 660
Law Kumar Singh India 22 303 1.6× 24 0.2× 296 4.4× 53 0.9× 32 0.5× 44 926
Muhammed Fahri Ünlerşen Türkiye 9 195 1.0× 126 1.1× 82 1.2× 203 3.3× 39 0.6× 15 658
Shankar Thawkar India 14 228 1.2× 24 0.2× 142 2.1× 44 0.7× 21 0.3× 23 511
Baljit Singh Khehra India 11 117 0.6× 77 0.7× 167 2.5× 96 1.5× 38 0.6× 40 453
V. Dhilip Kumar India 11 122 0.6× 65 0.6× 45 0.7× 175 2.8× 44 0.7× 36 539
Giulio Binetti Italy 12 63 0.3× 32 0.3× 26 0.4× 5 0.1× 591 9.7× 23 929

Countries citing papers authored by Pablo Escandell-Montero

Since Specialization
Citations

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

Fields of papers citing papers by Pablo Escandell-Montero

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pablo Escandell-Montero. 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 Pablo Escandell-Montero. The network helps show where Pablo Escandell-Montero may publish in the future.

Co-authorship network of co-authors of Pablo Escandell-Montero

This figure shows the co-authorship network connecting the top 25 collaborators of Pablo Escandell-Montero. A scholar is included among the top collaborators of Pablo Escandell-Montero 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 Pablo Escandell-Montero. Pablo Escandell-Montero 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.
Alvarez-Rodriguez, Unai, Lucas Lamata, Pablo Escandell-Montero, José D. Martín‐Guerrero, & E. Solano. (2016). Quantum Machine Learning without Measurements.. arXiv (Cornell University). 5 indexed citations
2.
Martínez-Martínez, José M., Pablo Escandell-Montero, Emilio Soria‐Olivas, José D. Martín‐Guerrero, & Antonio J. Serrano-López. (2016). A new visualization tool for data mining techniques. Progress in Artificial Intelligence. 5(2). 137–154. 5 indexed citations
3.
Martínez-Martínez, José M., et al.. (2016). Use of SOMs for footwear comfort evaluation. Neural Computing and Applications. 28(7). 1763–1773. 3 indexed citations
4.
Lorente, D., Francisco Martínez‐Martínez, María José Rupérez, et al.. (2016). A framework for modelling the biomechanical behaviour of the human liver during breathing in real time using machine learning. Expert Systems with Applications. 71. 342–357. 40 indexed citations
5.
Escandell-Montero, Pablo, D. Lorente, José M. Martínez-Martínez, et al.. (2016). Online fitted policy iteration based on extreme learning machines. Knowledge-Based Systems. 100. 200–211. 9 indexed citations
6.
Barbieri, C., Flavio Mari, Andrea Stopper, et al.. (2015). A new machine learning approach for predicting the response to anemia treatment in a large cohort of End Stage Renal Disease patients undergoing dialysis. Computers in Biology and Medicine. 61. 56–61. 59 indexed citations
7.
Carrasco, Juan J., et al.. (2015). ELM Regularized Method for Classification Problems. International Journal of Artificial Intelligence Tools. 25(1). 1550026–1550026. 8 indexed citations
8.
Escandell-Montero, Pablo, José M. Martínez-Martínez, Emilio Soria‐Olivas, Joan Vila‐Francés, & José D. Martín‐Guerrero. (2014). Ensembles of extreme learning machine networks for value prediction.. The European Symposium on Artificial Neural Networks. 1 indexed citations
9.
Martínez-Martínez, José M., Pablo Escandell-Montero, C. Barbieri, et al.. (2014). Prediction of the hemoglobin level in hemodialysis patients using machine learning techniques. Computer Methods and Programs in Biomedicine. 117(2). 208–217. 32 indexed citations
10.
Escandell-Montero, Pablo, José M. Martínez-Martínez, José D. Martín‐Guerrero, Emilio Soria‐Olivas, & Juan Gómez‐Sanchís. (2014). Least-squares temporal difference learning based on an extreme learning machine. Neurocomputing. 141. 37–45. 9 indexed citations
11.
Mateo, Fernando, et al.. (2013). Temperature Forecast in Buildings Using Machine Learning Techniques.. The European Symposium on Artificial Neural Networks. 3 indexed citations
12.
García‐Gómez, Juan M., Juan Gómez‐Sanchís, Pablo Escandell-Montero, Elies Fuster‐García, & Emilio Soria‐Olivas. (2013). Sparse Manifold Clustering and Embedding to discriminate gene expression profiles of glioblastoma and meningioma tumors. Computers in Biology and Medicine. 43(11). 1863–1869. 4 indexed citations
13.
Rosado-Muñoz, Alfredo, José M. Martínez-Martínez, Pablo Escandell-Montero, & Emilio Soria‐Olivas. (2013). Visual data mining with self-organising maps for ventricular fibrillation analysis. Computer Methods and Programs in Biomedicine. 111(2). 269–279. 9 indexed citations
14.
Gómez‐Sanchís, Juan, J. Blasco, Emilio Soria‐Olivas, et al.. (2013). Hyperspectral LCTF-based system for classification of decay in mandarins caused by Penicillium digitatum and Penicillium italicum using the most relevant bands and non-linear classifiers. Postharvest Biology and Technology. 82. 76–86. 63 indexed citations
15.
Mateo, Fernando, et al.. (2013). Machine Learning Techniques for Short-Term Elec tric Power Demand Prediction. 5 indexed citations
16.
Escandell-Montero, Pablo, et al.. (2012). Regularized Committee of Extreme Learning Machine for Regression Problems.. The European Symposium on Artificial Neural Networks. 5 indexed citations
17.
Martínez-Martínez, José M., Pablo Escandell-Montero, Emilio Soria‐Olivas, et al.. (2012). extended visualization method for classification trees.. The European Symposium on Artificial Neural Networks. 1 indexed citations
18.
Escandell-Montero, Pablo, et al.. (2011). Growing Hierarchical Sectors on Sectors. The European Symposium on Artificial Neural Networks. 2 indexed citations
19.
Martínez-Martínez, José M., Pablo Escandell-Montero, Emilio Soria‐Olivas, et al.. (2011). Sectors on sectors (SonS): A new hierarchical clustering visualization tool. 149. 304–309. 3 indexed citations
20.
Martínez-Martínez, José M., Pablo Escandell-Montero, Emilio Soria‐Olivas, et al.. (2011). Regularized extreme learning machine for regression problems. Neurocomputing. 74(17). 3716–3721. 159 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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