Marcelino Lázaro

594 total citations
39 papers, 418 citations indexed

About

Marcelino Lázaro is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering and Signal Processing. According to data from OpenAlex, Marcelino Lázaro has authored 39 papers receiving a total of 418 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Artificial Intelligence, 10 papers in Electrical and Electronic Engineering and 9 papers in Signal Processing. Recurrent topics in Marcelino Lázaro's work include Neural Networks and Applications (13 papers), Blind Source Separation Techniques (8 papers) and Distributed Sensor Networks and Detection Algorithms (6 papers). Marcelino Lázaro is often cited by papers focused on Neural Networks and Applications (13 papers), Blind Source Separation Techniques (8 papers) and Distributed Sensor Networks and Detection Algorithms (6 papers). Marcelino Lázaro collaborates with scholars based in Spain, United States and United Kingdom. Marcelino Lázaro's co-authors include Ignacio Santamarı́a, Anı́bal R. Figueiras-Vidal, C. Pantaleón, Deniz Erdoğmuş, José C. Prı́ncipe, Antonio Artés-Rodrı́guez, Kenneth E. Hild, Francisco Herrera, Fernando Pérez‐Cruz and Salvador García and has published in prestigious journals such as IEEE Transactions on Signal Processing, Expert Systems with Applications and Pattern Recognition.

In The Last Decade

Marcelino Lázaro

38 papers receiving 396 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Marcelino Lázaro Spain 14 204 146 106 77 58 39 418
Rueywen Liu United States 10 161 0.8× 129 0.9× 101 1.0× 71 0.9× 43 0.7× 43 397
Junan Yang China 13 286 1.4× 96 0.7× 79 0.7× 45 0.6× 23 0.4× 90 536
Charles C. Cavalcante Brazil 13 77 0.4× 324 2.2× 103 1.0× 33 0.4× 59 1.0× 82 549
Tirza Routtenberg Israel 17 301 1.5× 248 1.7× 293 2.8× 211 2.7× 81 1.4× 88 796
Jon Dattorro 6 61 0.3× 96 0.7× 114 1.1× 57 0.7× 99 1.7× 8 423
Shao-Po Wu United States 4 59 0.3× 181 1.2× 78 0.7× 153 2.0× 83 1.4× 5 595
Cheolwoo You South Korea 10 158 0.8× 291 2.0× 145 1.4× 42 0.5× 39 0.7× 72 478
Xujun Zhao China 13 237 1.2× 24 0.2× 106 1.0× 37 0.5× 30 0.5× 33 479
Chris Darken United States 7 170 0.8× 37 0.3× 32 0.3× 54 0.7× 36 0.6× 10 359
Pascal Bianchi France 15 191 0.9× 273 1.9× 64 0.6× 37 0.5× 123 2.1× 66 685

Countries citing papers authored by Marcelino Lázaro

Since Specialization
Citations

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

Fields of papers citing papers by Marcelino Lázaro

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marcelino Lázaro

This figure shows the co-authorship network connecting the top 25 collaborators of Marcelino Lázaro. A scholar is included among the top collaborators of Marcelino Lázaro 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 Marcelino Lázaro. Marcelino Lázaro 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.
Lázaro, Marcelino, et al.. (2024). COCOA: Cost-Optimized COunterfactuAl explanation method. Information Sciences. 670. 120616–120616. 1 indexed citations
2.
Lázaro, Marcelino & Anı́bal R. Figueiras-Vidal. (2023). Neural network for ordinal classification of imbalanced data by minimizing a Bayesian cost. Pattern Recognition. 137. 109303–109303. 17 indexed citations
3.
Lázaro, Marcelino, Francisco Herrera, & Anı́bal R. Figueiras-Vidal. (2020). Ensembles of cost-diverse Bayesian neural learners for imbalanced binary classification. Information Sciences. 520. 31–45. 13 indexed citations
4.
Lázaro, Marcelino, M.H. Hayes, & Anı́bal R. Figueiras-Vidal. (2017). Training neural network classifiers through Bayes risk minimization applying unidimensional Parzen windows. Pattern Recognition. 77. 204–215. 11 indexed citations
5.
González, Sergio, Salvador García, Marcelino Lázaro, Anı́bal R. Figueiras-Vidal, & Francisco Herrera. (2017). Class Switching according to Nearest Enemy Distance for learning from highly imbalanced data-sets. Pattern Recognition. 70. 12–24. 34 indexed citations
6.
Plata-Chaves, Jorge & Marcelino Lázaro. (2010). Closed-Form Error Exponent for the Neyman–Pearson Fusion of Dependent Local Decisions in a One-Dimensional Sensor Network. IEEE Transactions on Signal Processing. 59(3). 1239–1254. 4 indexed citations
7.
Lázaro, Marcelino, Matilde Sánchez-Fernández, & Antonio Artés-Rodrı́guez. (2009). Optimal Sensor Selection in Binary Heterogeneous Sensor Networks. IEEE Transactions on Signal Processing. 57(4). 1577–1587. 14 indexed citations
8.
Santiago‐Mozos, Ricardo, et al.. (2007). Real-time tracking and identification on an intelligent IR-based surveillance system. 277–282. 1 indexed citations
9.
Lázaro, Marcelino, et al.. (2006). Decentralized Detection In Dense Sensor Networks With Censored Transmissions. 4. 817–820. 1 indexed citations
10.
Lázaro, Marcelino, Fernando Pérez‐Cruz, & Antonio Artés-Rodrı́guez. (2005). Learning a function and its derivative forcing the support vector expansion. IEEE Signal Processing Letters. 12(3). 194–197. 3 indexed citations
11.
Vía, Javier, Ignacio Santamarı́a, & Marcelino Lázaro. (2004). Blind Restoration Of Binary Signals Using A Line Spectrum Fitting Approach. Zenodo (CERN European Organization for Nuclear Research). 461–464. 1 indexed citations
12.
Lázaro, Marcelino, Ignacio Santamarı́a, Fernando Pérez‐Cruz, & Antonio Artés-Rodrı́guez. (2004). Support vector machine for the simultaneous approximation of a function and its derivative. 189–198. 2 indexed citations
13.
Lázaro, Marcelino, Ignacio Santamarı́a, Javier Vía, & Deniz Erdoğmuş. (2004). Blind Equalization Of Multilevel Signals Using Support Vector Machines. European Signal Processing Conference. 41–44. 7 indexed citations
14.
Gispert, Juan Domingo, Santiago Reig, Javier Pascau, et al.. (2004). Inhomogeneity correction of magnetic resonance images by minimization of intensity overlapping. e-Archivo (Carlos III University of Madrid). 3. II–847. 3 indexed citations
15.
Lázaro, Marcelino, et al.. (2003). A new EM-based training algorithm for RBF networks. Neural Networks. 16(1). 69–77. 28 indexed citations
16.
Lázaro, Marcelino, Ignacio Santamarı́a, & C. Pantaleón. (2002). Neural networks for large and small-signal modeling of MESFET/HEMT transistors: a comparative study. 3. 1272–1277. 2 indexed citations
17.
Lázaro, Marcelino, Ignacio Santamarı́a, & C. Pantaleón. (2002). A smooth and derivable large-signal model for microwave HEMT transistors. 4. 713–716. 1 indexed citations
18.
Lázaro, Marcelino, Ignacio Santamarı́a, & C. Pantaleón. (2002). A regularized digital filtering technique for the simultaneous reconstruction of a function and its derivatives. 1. 67–70. 1 indexed citations
19.
Mediavilla, A., A. Tazón, José Antonio Martín Pereda, et al.. (2000). Neuronal architecture for waveguide inductive iris bandpass filter optimization. 395–399 vol.4. 10 indexed citations
20.
Lázaro, Marcelino, Ignacio Santamarı́a, C. Pantaleón, et al.. (2000). A modular neural network for global modeling of microwave transistors. 3 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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