David Cárdenas‐Peña

1.0k total citations
36 papers, 237 citations indexed

About

David Cárdenas‐Peña is a scholar working on Cognitive Neuroscience, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, David Cárdenas‐Peña has authored 36 papers receiving a total of 237 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Cognitive Neuroscience, 11 papers in Computer Vision and Pattern Recognition and 10 papers in Artificial Intelligence. Recurrent topics in David Cárdenas‐Peña's work include EEG and Brain-Computer Interfaces (10 papers), Medical Image Segmentation Techniques (7 papers) and Functional Brain Connectivity Studies (7 papers). David Cárdenas‐Peña is often cited by papers focused on EEG and Brain-Computer Interfaces (10 papers), Medical Image Segmentation Techniques (7 papers) and Functional Brain Connectivity Studies (7 papers). David Cárdenas‐Peña collaborates with scholars based in Colombia, France and United Kingdom. David Cárdenas‐Peña's co-authors include G. Castellanos-Domínguez, Álvaro A. Orozco, Étienne Decencière, Thomas Walter, Matthieu Faessel, Andrés Marino Álvarez-Meza, Mauricio Orozco‐Alzate, Paula González, Dominique Jeulin and Alzheimer’s Disease Neuroimaging Initiative and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Image Processing and Computer Methods in Applied Mechanics and Engineering.

In The Last Decade

David Cárdenas‐Peña

31 papers receiving 234 citations

Peers

David Cárdenas‐Peña

CVPR

PMH

Qiankun Zuo China

Said Ghoniemy Egypt

Margarita-Arimatea Díaz-Cortés Mexico

Zeeshan Hayder Australia

Juan E. Arco Spain

Ali Emami Iran

Linus Ericsson United Kingdom

Morteza Valizadeh Iran

Liyan Chen China

Qiankun Zuo China

David Cárdenas‐Peña

64 ×0.7

CVPR

67 ×1.2

92 ×2.0

11 ×0.4

30 ×1.3

PMH

Citations per year, relative to David Cárdenas‐Peña David Cárdenas‐Peña (= 1×) peers Qiankun Zuo

Countries citing papers authored by David Cárdenas‐Peña

Since Specialization

Citations

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

Fields of papers citing papers by David Cárdenas‐Peña

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Cárdenas‐Peña. 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 David Cárdenas‐Peña. The network helps show where David Cárdenas‐Peña may publish in the future.

Co-authorship network of co-authors of David Cárdenas‐Peña

This figure shows the co-authorship network connecting the top 25 collaborators of David Cárdenas‐Peña. A scholar is included among the top collaborators of David Cárdenas‐Peña 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 David Cárdenas‐Peña. David Cárdenas‐Peña is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Cárdenas‐Peña, David, et al.. (2025). Generalized cross-entropy for learning from crowds based on correlated chained Gaussian processes. Results in Engineering. 25. 103863–103863. 1 indexed citations

Orozco, Álvaro A., et al.. (2024). Implementación de un modelo predictive basado en redes neuronales convolucionales 3D en el paso de deterioro cognitivo leve a Alzheimer sobre imágenes por resonancia magnética. Revista EIA. 21(42). 1 indexed citations

Álvarez-Meza, Andrés Marino, et al.. (2024). Scalable and Interpretable Forecasting of Hydrological Time Series Based on Variational Gaussian Processes. Water. 16(14). 2006–2006.

Álvarez-Meza, Andrés Marino, et al.. (2024). Kreĭn twin support vector machines for imbalanced data classification. Pattern Recognition Letters. 182. 39–45. 7 indexed citations

Álvarez-Meza, Andrés Marino, et al.. (2024). Multimodal Explainability Using Class Activation Maps and Canonical Correlation for MI-EEG Deep Learning Classification. Applied Sciences. 14(23). 11208–11208. 1 indexed citations

Porras-Hurtado, Gloria Liliana, et al.. (2024). Therapeutic Hypothermia and Its Role in Preserving Brain Volume in Term Neonates with Perinatal Asphyxia. Journal of Clinical Medicine. 13(23). 7121–7121.

Álvarez-Meza, Andrés Marino, et al.. (2023). Posthoc Interpretability of Neural Responses by Grouping Subject Motor Imagery Skills Using CNN-Based Connectivity. Sensors. 23(5). 2750–2750. 3 indexed citations

Cárdenas‐Peña, David, et al.. (2023). Approximation of Weymouth Equation Using Mathematical Programs with Complementarity Constraints for Natural Gas Transportation. SHILAP Revista de lepidopterología. 91–91. 1 indexed citations

Álvarez-Meza, Andrés Marino, et al.. (2023). A Novel OpenBCI Framework for EEG-Based Neurophysiological Experiments. Sensors. 23(7). 3763–3763. 7 indexed citations

10.

Cárdenas‐Peña, David, et al.. (2021). Tdnn-Based Engine In-Cylinder Pressure Estimation from Shaft Velocity Spectral Representation. Sensors. 21(6). 2186–2186. 3 indexed citations

11.

Álvarez-Meza, Andrés Marino, et al.. (2021). Kernel-Based Phase Transfer Entropy with Enhanced Feature Relevance Analysis for Brain Computer Interfaces. Applied Sciences. 11(15). 6689–6689. 7 indexed citations

12.

Álvarez-Meza, Andrés Marino, et al.. (2021). Random Fourier Features-Based Deep Learning Improvement with Class Activation Interpretability for Nerve Structure Segmentation. Sensors. 21(22). 7741–7741. 11 indexed citations

13.

González, Paula, et al.. (2020). Classification of Categorical Data Based on the Chi-Square Dissimilarity and t-SNE. Computation. 8(4). 104–104. 13 indexed citations

14.

Cárdenas‐Peña, David, et al.. (2019). Adaptive Bayesian label fusion using kernel-based similarity metrics in hippocampus segmentation. Journal of Medical Imaging. 6(1). 1–1. 4 indexed citations

15.

Cárdenas‐Peña, David, et al.. (2018). Instance-Based Representation Using Multiple Kernel Learning for Predicting Conversion to Alzheimer Disease. International Journal of Neural Systems. 29(2). 1850042–1850042. 15 indexed citations

16.

Cárdenas‐Peña, David, et al.. (2017). Enhanced Data Representation by Kernel Metric Learning for Dementia Diagnosis. Frontiers in Neuroscience. 11. 413–413. 10 indexed citations

17.

Cárdenas‐Peña, David, et al.. (2017). Supervised kernel approach for automated learning using General Stochastic Networks. Engineering Applications of Artificial Intelligence. 68. 10–17. 5 indexed citations

18.

Cárdenas‐Peña, David, et al.. (2014). Tensor-product kernel-based representation encoding joint MRI view similarity. PubMed. 2014. 3897–3900. 1 indexed citations

19.

Cárdenas‐Peña, David, Mauricio Orozco‐Alzate, & G. Castellanos-Domínguez. (2012). Selection of time-variant features for earthquake classification at the Nevado-del-Ruiz volcano. Computers & Geosciences. 51. 293–304. 23 indexed citations

20.

Cárdenas‐Peña, David, et al.. (2012). Extraction of stationary components in biosignal discrimination. PubMed. 2012. 1–4. 1 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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