Enrique Domínguez

1.2k total citations
51 papers, 613 citations indexed

About

Enrique Domínguez is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology. According to data from OpenAlex, Enrique Domínguez has authored 51 papers receiving a total of 613 indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Computer Vision and Pattern Recognition, 18 papers in Artificial Intelligence and 9 papers in Media Technology. Recurrent topics in Enrique Domínguez's work include Video Surveillance and Tracking Methods (21 papers), Advanced Image and Video Retrieval Techniques (8 papers) and Image and Signal Denoising Methods (7 papers). Enrique Domínguez is often cited by papers focused on Video Surveillance and Tracking Methods (21 papers), Advanced Image and Video Retrieval Techniques (8 papers) and Image and Signal Denoising Methods (7 papers). Enrique Domínguez collaborates with scholars based in Spain, United Kingdom and United States. Enrique Domínguez's co-authors include Ezequiel López‐Rubio, Karl Thurnhofer‐Hemsi, Rafael Marcos Luque‐Baena, Esteban J. Palomo, Miguel A. Molina‐Cabello, David Elizondo, Enrique Alba, Kayvan Najarian, S. M. Reza Soroushmehr and José M. Jerez and has published in prestigious journals such as IEEE Access, Sensors and Neurocomputing.

In The Last Decade

Enrique Domínguez

49 papers receiving 576 citations

Peers

Enrique Domínguez

CVPR

ONCOL

EPIDE

Mehrez Marzougui Saudi Arabia

Van-Dung Hoang South Korea

Tianyi Li China

Javad Rahebi Türkiye

Walid Barhoumi Tunisia

Sandeep Kumar Mathivanan India

J. Dinesh Peter India

Marwa Obayya Saudi Arabia

Kwang-Baek Kim South Korea

Lituan Wang China

Mehrez Marzougui Saudi Arabia

Enrique Domínguez

180 ×0.7

CVPR

136 ×0.6

88 ×0.6

ONCOL

49 ×0.8

EPIDE

48 ×1.0

Citations per year, relative to Enrique Domínguez Enrique Domínguez (= 1×) peers Mehrez Marzougui

Countries citing papers authored by Enrique Domínguez

Since Specialization

Citations

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

Fields of papers citing papers by Enrique Domínguez

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Enrique Domínguez

This figure shows the co-authorship network connecting the top 25 collaborators of Enrique Domínguez. A scholar is included among the top collaborators of Enrique Domínguez 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 Enrique Domínguez. Enrique Domínguez 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

Thurnhofer‐Hemsi, Karl, et al.. (2024). Deep Learning Models for Gait Event Prediction. 11. 1–8. 1 indexed citations

Palomo, Esteban J., et al.. (2023). A convolutional autoencoder and a neural gas model based on Bregman divergences for hierarchical color quantization. Neurocomputing. 544. 126288–126288. 2 indexed citations

Thurnhofer‐Hemsi, Karl, et al.. (2023). Analysis and Recognition of Human Gait Activity Based on Multimodal Sensors. Mathematics. 11(6). 1538–1538. 3 indexed citations

Domínguez, Enrique, et al.. (2023). An uncertainty estimator method based on the application of feature density to classify mammograms for breast cancer detection. Neural Computing and Applications. 35(30). 22151–22161. 4 indexed citations

Medina, Daniel, et al.. (2023). Detection of dangerously approaching vehicles over onboard cameras by speed estimation from apparent size. Neurocomputing. 567. 127057–127057. 3 indexed citations

Palomo, Esteban J., et al.. (2020). Image Clustering Using a Growing Neural Gas with Forbidden Regions. 1–7. 2 indexed citations

Thurnhofer‐Hemsi, Karl & Enrique Domínguez. (2020). A Convolutional Neural Network Framework for Accurate Skin Cancer Detection. Neural Processing Letters. 53(5). 3073–3093. 111 indexed citations

Domínguez, Enrique & Alfredo Marı́n. (2020). Discrete ordered median problem with induced order. Top. 28(3). 793–813. 2 indexed citations

Thurnhofer‐Hemsi, Karl, Ezequiel López‐Rubio, Enrique Domínguez, Rafael Marcos Luque‐Baena, & Núria Roé-Vellvé. (2019). Deep learning-based super-resolution of 3D magnetic resonance images by regularly spaced shifting. Neurocomputing. 398. 314–327. 12 indexed citations

10.

Thurnhofer‐Hemsi, Karl, Ezequiel López‐Rubio, Núria Roé-Vellvé, Enrique Domínguez, & Miguel A. Molina‐Cabello. (2018). Super-resolution of 3D Magnetic Resonance Images by Random Shifting and Convolutional Neural Networks. 1–8. 4 indexed citations

11.

Molina‐Cabello, Miguel A., et al.. (2018). Comparación de marcos de trabajo de Aprendizaje Profundo para la detección de objetos. Dialnet (Universidad de la Rioja). 1219–1224.

12.

Molina‐Cabello, Miguel A., et al.. (2017). A Growing Neural Gas Approach to Classify Vehicles in Traffic Environments. 7(3). 1–12. 1 indexed citations

13.

Thurnhofer‐Hemsi, Karl, Ezequiel López‐Rubio, Enrique Domínguez, Rafael Marcos Luque‐Baena, & Miguel A. Molina‐Cabello. (2017). Panorama construction for PTZ camera surveillance with the neural gas network. Expert Systems. 35(2). 3 indexed citations

14.

López‐Rubio, Ezequiel, et al.. (2016). The effect of noise on foreground detection algorithms. Artificial Intelligence Review. 49(3). 407–438. 8 indexed citations

15.

López‐Rubio, Ezequiel, et al.. (2014). Color space selection for self-organizing map based foreground detection in video sequences. 3347–3354. 6 indexed citations

16.

López‐Rubio, Ezequiel, Esteban J. Palomo, & Enrique Domínguez. (2014). Robust self-organization with M-estimators. Neurocomputing. 151. 408–423. 6 indexed citations

17.

Palomo, Esteban J., et al.. (2012). Image Compression and Video Segmentation Using Hierarchical Self-Organization. Neural Processing Letters. 37(1). 69–87. 5 indexed citations

18.

Luque‐Baena, Rafael Marcos, Enrique Domínguez, Esteban J. Palomo, & J.T. Entrambasaguas. (2010). An ART-type network approach for video object detection. The European Symposium on Artificial Neural Networks. 10 indexed citations

19.

Palomo, Esteban J., et al.. (2010). An anomaly detection system using a GHSOM-1. 4. 1–7. 4 indexed citations

20.

Domínguez, Enrique, José Muñoz Pérez, & José M. Jerez. (2003). Neural Network Algorithms for the p-Median Problem. The European Symposium on Artificial Neural Networks. 385–392. 6 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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