Emilio Soria‐Olivas
- Media Technology top 1%
- Remote-Sensing Image Classification 7
- Analytical Chemistry top 1%
- Spectroscopy and Chemometric Analyses 8
- Artificial Intelligence top 2%
- Neural Networks and Applications 20
- Machine Learning and ELM 14
- Imbalanced Data Classification Techniques 6
- Health Informatics top 5%
- Signal Processing top 5%
- Blind Source Separation Techniques 8
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- Face and Expression Recognition 12
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- Artificial Intelligence in Healthcare 6
Emilio Soria‐Olivas
118 papers receiving 2.4k citations
Peers
Comparison fields: 5 of 182
- Media Technology 278
- Analytical Chemistry 284
- Artificial Intelligence 654
- Health Informatics 24
- Signal Processing 186
Countries citing papers authored by Emilio Soria‐Olivas
This map shows the geographic impact of Emilio Soria‐Olivas'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 Emilio Soria‐Olivas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Emilio Soria‐Olivas more than expected).
Fields of papers citing papers by Emilio Soria‐Olivas
This network shows the impact of papers produced by Emilio Soria‐Olivas. 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 Emilio Soria‐Olivas. The network helps show where Emilio Soria‐Olivas may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Emilio Soria‐Olivas, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 7 | |
| 3 | 2021 | 6 | |
| 4 | 2021 | 3 | |
| 5 | 2021 | 22 | |
| 6 | 2019 | 18 | |
| 7 | Randomized Machine Learning Approaches: Recent Developments and Challenges | 2017 | 21 |
| 8 | Multi-step strategy for mortality assessment in cardiovascular risk patients with imbalanced data. | 2016 | 1 |
| 9 | Ensembles of extreme learning machine networks for value prediction. | 2014 | 1 |
| 10 | 2014 | 32 | |
| 11 | Temperature Forecast in Buildings Using Machine Learning Techniques. | 2013 | 3 |
| 12 | Regularized Committee of Extreme Learning Machine for Regression Problems. | 2012 | 5 |
| 13 | extended visualization method for classification trees. | 2012 | 1 |
| 14 | Growing Hierarchical Sectors on Sectors | 2011 | 2 |
| 15 | Neural models for the analysis of kidney disease patients. | 2010 | 2 |
| 16 | Comparative study of several Fir median hybrid filters for blink noise removal in Electrooculograms | 2008 | 11 |
| 17 | Implementation Challenges in Complex Adaptive Systems. | 2005 | 0 |
| 18 | 2004 | 15 | |
| 19 | 2003 | 33 | |
| 20 | 2002 | 20 |
About Emilio Soria‐Olivas
Emilio Soria‐Olivas is a scholar working on Artificial Intelligence, Signal Processing and Health Information Management, having authored 122 papers that have together received 2.5k indexed citations. Recurring topics across this work include Neural Networks and Applications (20 papers), Machine Learning and ELM (14 papers), Face and Expression Recognition (12 papers), Blind Source Separation Techniques (8 papers), Spectroscopy and Chemometric Analyses (8 papers), Remote-Sensing Image Classification (7 papers), Artificial Intelligence in Healthcare (6 papers) and Imbalanced Data Classification Techniques (6 papers). The work is most often cited by research in Media Technology (278 citations), Analytical Chemistry (284 citations) and Artificial Intelligence (654 citations). Emilio Soria‐Olivas has collaborated with scholars based in Spain, United States and Italy. Frequent co-authors include José D. Martín‐Guerrero, Juan Gómez‐Sanchís, Gustau Camps‐Valls, Antonio J. Serrano-López, Rafael Magdalena‐Benedito, Javier Calpe‐Maravilla, Marcelino Martínez‐Sober, Luis Gómez‐Chova, José M. Martínez-Martínez and Pablo Escandell-Montero. Their work appears in journals such as PLoS ONE, Neurology and Scientific Reports.
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.